{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/stuartturnbulldugarte/Dropbox/Pink Turnout Paper/R&P/RP_Logfile.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}24 Jul 2020, 13:56:17

{com}. do "/var/folders/g7/hp9p445x6kdbps08kwbb19gh0000gn/T//SD03027.000000"
{txt}
{com}. 
. //Table 1//
. logit interest i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-87167.942}  
Iteration 1:{space 3}log pseudolikelihood = {res:-75709.179}  
Iteration 2:{space 3}log pseudolikelihood = {res:-75634.005}  
Iteration 3:{space 3}log pseudolikelihood = {res:-75633.892}  
Iteration 4:{space 3}log pseudolikelihood = {res:-75633.892}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,726
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(9)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-75633.892{txt}{col 49}Pseudo R2{col 67}= {res}    0.1323

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}     interested{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1276096{col 29}{space 2} .0220308{col 40}{space 1}    5.79{col 49}{space 3}0.000{col 57}{space 4}   .08443{col 70}{space 3} .1707893
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .6020354{col 29}{space 2}  .025027{col 40}{space 1}   24.06{col 49}{space 3}0.000{col 57}{space 4} .5529834{col 70}{space 3} .6510874
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0254423{col 29}{space 2} .0039331{col 40}{space 1}    6.47{col 49}{space 3}0.000{col 57}{space 4} .0177335{col 70}{space 3} .0331511
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .1514151{col 29}{space 2}  .012987{col 40}{space 1}   11.66{col 49}{space 3}0.000{col 57}{space 4} .1259609{col 70}{space 3} .1768692
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .2345643{col 29}{space 2} .0306337{col 40}{space 1}    7.66{col 49}{space 3}0.000{col 57}{space 4} .1745233{col 70}{space 3} .2946053
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0257435{col 29}{space 2} .0477422{col 40}{space 1}    0.54{col 49}{space 3}0.590{col 57}{space 4}-.0678294{col 70}{space 3} .1193165
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .3837853{col 29}{space 2} .0498282{col 40}{space 1}    7.70{col 49}{space 3}0.000{col 57}{space 4} .2861239{col 70}{space 3} .4814467
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0707536{col 29}{space 2} .0309065{col 40}{space 1}   -2.29{col 49}{space 3}0.022{col 57}{space 4}-.1313293{col 70}{space 3}-.0101779
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} .0362094{col 29}{space 2} .0521798{col 40}{space 1}    0.69{col 49}{space 3}0.488{col 57}{space 4} -.066061{col 70}{space 3} .1384799
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.1424878{col 29}{space 2} .0596173{col 40}{space 1}   -2.39{col 49}{space 3}0.017{col 57}{space 4}-.2593355{col 70}{space 3}-.0256401
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} -4.16282{col 29}{space 2} .4328785{col 40}{space 1}   -9.62{col 49}{space 3}0.000{col 57}{space 4}-5.011247{col 70}{space 3}-3.314394
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit voted i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-55884.965}  
Iteration 1:{space 3}log pseudolikelihood = {res:-50526.931}  
Iteration 2:{space 3}log pseudolikelihood = {res:-50130.429}  
Iteration 3:{space 3}log pseudolikelihood = {res:-50128.446}  
Iteration 4:{space 3}log pseudolikelihood = {res:-50128.444}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   105,715
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-50128.444{txt}{col 49}Pseudo R2{col 67}= {res}    0.1030

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}          voted{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1260183{col 29}{space 2} .0252596{col 40}{space 1}    4.99{col 49}{space 3}0.000{col 57}{space 4} .0765105{col 70}{space 3} .1755262
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0120327{col 29}{space 2} .0185988{col 40}{space 1}    0.65{col 49}{space 3}0.518{col 57}{space 4}-.0244202{col 70}{space 3} .0484856
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{txt}{space 12}swi {c |}{col 17}{res}{space 2} .3482535{col 29}{space 2} .0710793{col 40}{space 1}    4.90{col 49}{space 3}0.000{col 57}{space 4} .2089407{col 70}{space 3} .4875663
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.3439682{col 29}{space 2} .1069613{col 40}{space 1}   -3.22{col 49}{space 3}0.001{col 57}{space 4}-.5536086{col 70}{space 3}-.1343279
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} -.144925{col 29}{space 2} .2034272{col 40}{space 1}   -0.71{col 49}{space 3}0.476{col 57}{space 4} -.543635{col 70}{space 3} .2537851
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.2350516{col 29}{space 2}   .03996{col 40}{space 1}   -5.88{col 49}{space 3}0.000{col 57}{space 4}-.3133717{col 70}{space 3}-.1567315
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.2576402{col 29}{space 2} .0256354{col 40}{space 1}  -10.05{col 49}{space 3}0.000{col 57}{space 4}-.3078846{col 70}{space 3}-.2073957
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .1318329{col 29}{space 2} .0301645{col 40}{space 1}    4.37{col 49}{space 3}0.000{col 57}{space 4} .0727115{col 70}{space 3} .1909543
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-2.018328{col 29}{space 2} .3997916{col 40}{space 1}   -5.05{col 49}{space 3}0.000{col 57}{space 4}-2.801905{col 70}{space 3}-1.234751
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. //Figure 1//
. logit interest i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-87167.942}  
Iteration 1:{space 3}log pseudolikelihood = {res:-75709.179}  
Iteration 2:{space 3}log pseudolikelihood = {res:-75634.005}  
Iteration 3:{space 3}log pseudolikelihood = {res:-75633.892}  
Iteration 4:{space 3}log pseudolikelihood = {res:-75633.892}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,726
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(9)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-75633.892{txt}{col 49}Pseudo R2{col 67}= {res}    0.1323

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}     interested{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1276096{col 29}{space 2} .0220308{col 40}{space 1}    5.79{col 49}{space 3}0.000{col 57}{space 4}   .08443{col 70}{space 3} .1707893
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .6020354{col 29}{space 2}  .025027{col 40}{space 1}   24.06{col 49}{space 3}0.000{col 57}{space 4} .5529834{col 70}{space 3} .6510874
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0254423{col 29}{space 2} .0039331{col 40}{space 1}    6.47{col 49}{space 3}0.000{col 57}{space 4} .0177335{col 70}{space 3} .0331511
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .1514151{col 29}{space 2}  .012987{col 40}{space 1}   11.66{col 49}{space 3}0.000{col 57}{space 4} .1259609{col 70}{space 3} .1768692
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .2345643{col 29}{space 2} .0306337{col 40}{space 1}    7.66{col 49}{space 3}0.000{col 57}{space 4} .1745233{col 70}{space 3} .2946053
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0257435{col 29}{space 2} .0477422{col 40}{space 1}    0.54{col 49}{space 3}0.590{col 57}{space 4}-.0678294{col 70}{space 3} .1193165
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .3837853{col 29}{space 2} .0498282{col 40}{space 1}    7.70{col 49}{space 3}0.000{col 57}{space 4} .2861239{col 70}{space 3} .4814467
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0707536{col 29}{space 2} .0309065{col 40}{space 1}   -2.29{col 49}{space 3}0.022{col 57}{space 4}-.1313293{col 70}{space 3}-.0101779
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} .0362094{col 29}{space 2} .0521798{col 40}{space 1}    0.69{col 49}{space 3}0.488{col 57}{space 4} -.066061{col 70}{space 3} .1384799
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.1424878{col 29}{space 2} .0596173{col 40}{space 1}   -2.39{col 49}{space 3}0.017{col 57}{space 4}-.2593355{col 70}{space 3}-.0256401
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .6084209{col 29}{space 2} .0203694{col 40}{space 1}   29.87{col 49}{space 3}0.000{col 57}{space 4} .5684976{col 70}{space 3} .6483441
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .4115044{col 29}{space 2} .0272077{col 40}{space 1}   15.12{col 49}{space 3}0.000{col 57}{space 4} .3581783{col 70}{space 3} .4648305
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} -4.16282{col 29}{space 2} .4328785{col 40}{space 1}   -9.62{col 49}{space 3}0.000{col 57}{space 4}-5.011247{col 70}{space 3}-3.314394
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,726
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(interested), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0261504{col 29}{space 2} .0044228{col 40}{space 1}    5.91{col 49}{space 3}0.000{col 57}{space 4} .0174819{col 70}{space 3} .0348189
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .1259232{col 29}{space 2} .0040341{col 40}{space 1}   31.22{col 49}{space 3}0.000{col 57}{space 4} .1180166{col 70}{space 3} .1338298
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0052411{col 29}{space 2} .0007448{col 40}{space 1}    7.04{col 49}{space 3}0.000{col 57}{space 4} .0037813{col 70}{space 3} .0067009
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0311915{col 29}{space 2} .0022385{col 40}{space 1}   13.93{col 49}{space 3}0.000{col 57}{space 4} .0268042{col 70}{space 3} .0355789
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0483203{col 29}{space 2} .0058271{col 40}{space 1}    8.29{col 49}{space 3}0.000{col 57}{space 4} .0368993{col 70}{space 3} .0597412
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0053115{col 29}{space 2} .0097749{col 40}{space 1}    0.54{col 49}{space 3}0.587{col 57}{space 4} -.013847{col 70}{space 3}   .02447
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .0775729{col 29}{space 2}  .009092{col 40}{space 1}    8.53{col 49}{space 3}0.000{col 57}{space 4} .0597528{col 70}{space 3}  .095393
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0146467{col 29}{space 2}  .006485{col 40}{space 1}   -2.26{col 49}{space 3}0.024{col 57}{space 4} -.027357{col 70}{space 3}-.0019364
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} .0074678{col 29}{space 2} .0107419{col 40}{space 1}    0.70{col 49}{space 3}0.487{col 57}{space 4} -.013586{col 70}{space 3} .0285216
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.0294435{col 29}{space 2} .0126906{col 40}{space 1}   -2.32{col 49}{space 3}0.020{col 57}{space 4}-.0543166{col 70}{space 3}-.0045705
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.0230035{col 29}{space 2} .0010504{col 40}{space 1}  -21.90{col 49}{space 3}0.000{col 57}{space 4}-.0250622{col 70}{space 3}-.0209448
{txt}{space 10}4012  {c |}{col 17}{res}{space 2}-.0156233{col 29}{space 2} .0027741{col 40}{space 1}   -5.63{col 49}{space 3}0.000{col 57}{space 4}-.0210604{col 70}{space 3}-.0101863
{txt}{space 10}4016  {c |}{col 17}{res}{space 2} .0221999{col 29}{space 2}   .00344{col 40}{space 1}    6.45{col 49}{space 3}0.000{col 57}{space 4} .0154577{col 70}{space 3} .0289421
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.0092841{col 29}{space 2} .0034078{col 40}{space 1}   -2.72{col 49}{space 3}0.006{col 57}{space 4}-.0159632{col 70}{space 3} -.002605
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.0215829{col 29}{space 2} .0042274{col 40}{space 1}   -5.11{col 49}{space 3}0.000{col 57}{space 4}-.0298685{col 70}{space 3}-.0132974
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.0119442{col 29}{space 2} .0045707{col 40}{space 1}   -2.61{col 49}{space 3}0.009{col 57}{space 4}-.0209026{col 70}{space 3}-.0029858
{txt}{space 10}4032  {c |}{col 17}{res}{space 2}-.0372736{col 29}{space 2} .0059018{col 40}{space 1}   -6.32{col 49}{space 3}0.000{col 57}{space 4}-.0488409{col 70}{space 3}-.0257064
{txt}{space 10}8008  {c |}{col 17}{res}{space 2} .1866132{col 29}{space 2} .0017746{col 40}{space 1}  105.16{col 49}{space 3}0.000{col 57}{space 4}  .183135{col 70}{space 3} .1900914
{txt}{space 10}8016  {c |}{col 17}{res}{space 2} .1905854{col 29}{space 2} .0016008{col 40}{space 1}  119.06{col 49}{space 3}0.000{col 57}{space 4} .1874479{col 70}{space 3}  .193723
{txt}{space 10}8024  {c |}{col 17}{res}{space 2} .0706239{col 29}{space 2} .0058984{col 40}{space 1}   11.97{col 49}{space 3}0.000{col 57}{space 4} .0590632{col 70}{space 3} .0821846
{txt}{space 10}8032  {c |}{col 17}{res}{space 2} .1384849{col 29}{space 2} .0016437{col 40}{space 1}   84.25{col 49}{space 3}0.000{col 57}{space 4} .1352632{col 70}{space 3} .1417065
{txt}{space 10}8040  {c |}{col 17}{res}{space 2} .1337562{col 29}{space 2} .0025549{col 40}{space 1}   52.35{col 49}{space 3}0.000{col 57}{space 4} .1287487{col 70}{space 3} .1387637
{txt}{space 10}8048  {c |}{col 17}{res}{space 2} .1585023{col 29}{space 2} .0028682{col 40}{space 1}   55.26{col 49}{space 3}0.000{col 57}{space 4} .1528807{col 70}{space 3}  .164124
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{txt}{space 9}14014  {c |}{col 17}{res}{space 2} .1664137{col 29}{space 2} .0020633{col 40}{space 1}   80.65{col 49}{space 3}0.000{col 57}{space 4} .1623697{col 70}{space 3} .1704576
{txt}{space 9}14028  {c |}{col 17}{res}{space 2} .1090992{col 29}{space 2} .0019282{col 40}{space 1}   56.58{col 49}{space 3}0.000{col 57}{space 4}   .10532{col 70}{space 3} .1128784
{txt}{space 9}14042  {c |}{col 17}{res}{space 2} .0606783{col 29}{space 2} .0021454{col 40}{space 1}   28.28{col 49}{space 3}0.000{col 57}{space 4} .0564734{col 70}{space 3} .0648832
{txt}{space 9}14056  {c |}{col 17}{res}{space 2} .1066808{col 29}{space 2} .0049643{col 40}{space 1}   21.49{col 49}{space 3}0.000{col 57}{space 4} .0969509{col 70}{space 3} .1164108
{txt}{space 9}14070  {c |}{col 17}{res}{space 2} .0919859{col 29}{space 2} .0043049{col 40}{space 1}   21.37{col 49}{space 3}0.000{col 57}{space 4} .0835484{col 70}{space 3} .1004235
{txt}{space 9}14084  {c |}{col 17}{res}{space 2} .1122779{col 29}{space 2} .0051323{col 40}{space 1}   21.88{col 49}{space 3}0.000{col 57}{space 4} .1022188{col 70}{space 3}  .122337
{txt}{space 9}14098  {c |}{col 17}{res}{space 2} .1356954{col 29}{space 2} .0070251{col 40}{space 1}   19.32{col 49}{space 3}0.000{col 57}{space 4} .1219265{col 70}{space 3} .1494644
{txt}{space 9}14112  {c |}{col 17}{res}{space 2} .1421316{col 29}{space 2} .0073897{col 40}{space 1}   19.23{col 49}{space 3}0.000{col 57}{space 4}  .127648{col 70}{space 3} .1566152
{txt}{space 9}20020  {c |}{col 17}{res}{space 2} -.198628{col 29}{space 2}  .004576{col 40}{space 1}  -43.41{col 49}{space 3}0.000{col 57}{space 4}-.2075968{col 70}{space 3}-.1896592
{txt}{space 9}20040  {c |}{col 17}{res}{space 2}-.1309173{col 29}{space 2} .0039178{col 40}{space 1}  -33.42{col 49}{space 3}0.000{col 57}{space 4}-.1385961{col 70}{space 3}-.1232386
{txt}{space 9}20060  {c |}{col 17}{res}{space 2}-.1790737{col 29}{space 2} .0024564{col 40}{space 1}  -72.90{col 49}{space 3}0.000{col 57}{space 4}-.1838881{col 70}{space 3}-.1742593
{txt}{space 9}20080  {c |}{col 17}{res}{space 2}-.1672219{col 29}{space 2} .0034224{col 40}{space 1}  -48.86{col 49}{space 3}0.000{col 57}{space 4}-.1739296{col 70}{space 3}-.1605142
{txt}{space 9}20100  {c |}{col 17}{res}{space 2}-.1729307{col 29}{space 2} .0013574{col 40}{space 1} -127.40{col 49}{space 3}0.000{col 57}{space 4}-.1755911{col 70}{space 3}-.1702703
{txt}{space 9}20120  {c |}{col 17}{res}{space 2}-.1065658{col 29}{space 2} .0021794{col 40}{space 1}  -48.90{col 49}{space 3}0.000{col 57}{space 4}-.1108374{col 70}{space 3}-.1022943
{txt}{space 9}20140  {c |}{col 17}{res}{space 2}-.0681634{col 29}{space 2} .0026065{col 40}{space 1}  -26.15{col 49}{space 3}0.000{col 57}{space 4}-.0732722{col 70}{space 3}-.0630547
{txt}{space 9}20160  {c |}{col 17}{res}{space 2}-.0968798{col 29}{space 2} .0031363{col 40}{space 1}  -30.89{col 49}{space 3}0.000{col 57}{space 4}-.1030268{col 70}{space 3}-.0907327
{txt}{space 9}22022  {c |}{col 17}{res}{space 2} .0256895{col 29}{space 2} .0018442{col 40}{space 1}   13.93{col 49}{space 3}0.000{col 57}{space 4}  .022075{col 70}{space 3}  .029304
{txt}{space 9}22044  {c |}{col 17}{res}{space 2}-.0190011{col 29}{space 2} .0015468{col 40}{space 1}  -12.28{col 49}{space 3}0.000{col 57}{space 4}-.0220327{col 70}{space 3}-.0159696
{txt}{space 9}22066  {c |}{col 17}{res}{space 2}-.0160127{col 29}{space 2} .0017512{col 40}{space 1}   -9.14{col 49}{space 3}0.000{col 57}{space 4}-.0194451{col 70}{space 3}-.0125804
{txt}{space 9}22088  {c |}{col 17}{res}{space 2}-.0147696{col 29}{space 2} .0024698{col 40}{space 1}   -5.98{col 49}{space 3}0.000{col 57}{space 4}-.0196103{col 70}{space 3}-.0099289
{txt}{space 9}22110  {c |}{col 17}{res}{space 2} -.019903{col 29}{space 2} .0033785{col 40}{space 1}   -5.89{col 49}{space 3}0.000{col 57}{space 4}-.0265248{col 70}{space 3}-.0132812
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{txt}{space 9}48048  {c |}{col 17}{res}{space 2}-.0100259{col 29}{space 2} .0022602{col 40}{space 1}   -4.44{col 49}{space 3}0.000{col 57}{space 4}-.0144558{col 70}{space 3} -.005596
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{txt}{space 9}48144  {c |}{col 17}{res}{space 2}-.0451262{col 29}{space 2}  .003759{col 40}{space 1}  -12.00{col 49}{space 3}0.000{col 57}{space 4}-.0524937{col 70}{space 3}-.0377588
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{txt}{space 9}52104  {c |}{col 17}{res}{space 2}-.0058908{col 29}{space 2} .0154888{col 40}{space 1}   -0.38{col 49}{space 3}0.704{col 57}{space 4}-.0362482{col 70}{space 3} .0244666
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{txt}{space 9}56280  {c |}{col 17}{res}{space 2} .0781906{col 29}{space 2} .0042962{col 40}{space 1}   18.20{col 49}{space 3}0.000{col 57}{space 4} .0697702{col 70}{space 3} .0866111
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{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .1289889{col 29}{space 2} .0060846{col 40}{space 1}   21.20{col 49}{space 3}0.000{col 57}{space 4} .1170632{col 70}{space 3} .1409145
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .0884464{col 29}{space 2} .0070791{col 40}{space 1}   12.49{col 49}{space 3}0.000{col 57}{space 4} .0745715{col 70}{space 3} .1023212
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store interest1
{txt}
{com}. 
. logit voted i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-55884.965}  
Iteration 1:{space 3}log pseudolikelihood = {res:-50526.931}  
Iteration 2:{space 3}log pseudolikelihood = {res:-50130.429}  
Iteration 3:{space 3}log pseudolikelihood = {res:-50128.446}  
Iteration 4:{space 3}log pseudolikelihood = {res:-50128.444}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   105,715
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-50128.444{txt}{col 49}Pseudo R2{col 67}= {res}    0.1030

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}          voted{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1260183{col 29}{space 2} .0252596{col 40}{space 1}    4.99{col 49}{space 3}0.000{col 57}{space 4} .0765105{col 70}{space 3} .1755262
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0120327{col 29}{space 2} .0185988{col 40}{space 1}    0.65{col 49}{space 3}0.518{col 57}{space 4}-.0244202{col 70}{space 3} .0484856
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0458195{col 29}{space 2} .0045588{col 40}{space 1}   10.05{col 49}{space 3}0.000{col 57}{space 4} .0368844{col 70}{space 3} .0547547
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0921837{col 29}{space 2} .0150784{col 40}{space 1}    6.11{col 49}{space 3}0.000{col 57}{space 4} .0626307{col 70}{space 3} .1217368
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .3482535{col 29}{space 2} .0710793{col 40}{space 1}    4.90{col 49}{space 3}0.000{col 57}{space 4} .2089407{col 70}{space 3} .4875663
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.3439682{col 29}{space 2} .1069613{col 40}{space 1}   -3.22{col 49}{space 3}0.001{col 57}{space 4}-.5536086{col 70}{space 3}-.1343279
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} -.144925{col 29}{space 2} .2034272{col 40}{space 1}   -0.71{col 49}{space 3}0.476{col 57}{space 4} -.543635{col 70}{space 3} .2537851
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.2350516{col 29}{space 2}   .03996{col 40}{space 1}   -5.88{col 49}{space 3}0.000{col 57}{space 4}-.3133717{col 70}{space 3}-.1567315
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.2576402{col 29}{space 2} .0256354{col 40}{space 1}  -10.05{col 49}{space 3}0.000{col 57}{space 4}-.3078846{col 70}{space 3}-.2073957
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .1318329{col 29}{space 2} .0301645{col 40}{space 1}    4.37{col 49}{space 3}0.000{col 57}{space 4} .0727115{col 70}{space 3} .1909543
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2} .4994795{col 29}{space 2} .0217838{col 40}{space 1}   22.93{col 49}{space 3}0.000{col 57}{space 4} .4567842{col 70}{space 3} .5421749
{txt}{space 10}4012  {c |}{col 17}{res}{space 2} .3525491{col 29}{space 2}   .02194{col 40}{space 1}   16.07{col 49}{space 3}0.000{col 57}{space 4} .3095474{col 70}{space 3} .3955507
{txt}{space 10}4016  {c |}{col 17}{res}{space 2} .3055592{col 29}{space 2} .0120445{col 40}{space 1}   25.37{col 49}{space 3}0.000{col 57}{space 4} .2819524{col 70}{space 3}  .329166
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.0475973{col 29}{space 2} .0170309{col 40}{space 1}   -2.79{col 49}{space 3}0.005{col 57}{space 4}-.0809772{col 70}{space 3}-.0142174
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.1673574{col 29}{space 2} .0163189{col 40}{space 1}  -10.26{col 49}{space 3}0.000{col 57}{space 4} -.199342{col 70}{space 3}-.1353729
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.1506421{col 29}{space 2} .0191067{col 40}{space 1}   -7.88{col 49}{space 3}0.000{col 57}{space 4}-.1880905{col 70}{space 3}-.1131936
{txt}{space 10}4032  {c |}{col 17}{res}{space 2} .0072561{col 29}{space 2} .0235094{col 40}{space 1}    0.31{col 49}{space 3}0.758{col 57}{space 4}-.0388215{col 70}{space 3} .0533338
{txt}{space 10}8008  {c |}{col 17}{res}{space 2}-1.294697{col 29}{space 2} .0156108{col 40}{space 1}  -82.94{col 49}{space 3}0.000{col 57}{space 4}-1.325294{col 70}{space 3}-1.264101
{txt}{space 10}8016  {c |}{col 17}{res}{space 2}-1.280069{col 29}{space 2} .0142295{col 40}{space 1}  -89.96{col 49}{space 3}0.000{col 57}{space 4}-1.307959{col 70}{space 3} -1.25218
{txt}{space 10}8024  {c |}{col 17}{res}{space 2}-1.750191{col 29}{space 2} .0463098{col 40}{space 1}  -37.79{col 49}{space 3}0.000{col 57}{space 4}-1.840956{col 70}{space 3}-1.659425
{txt}{space 10}8032  {c |}{col 17}{res}{space 2}-1.578627{col 29}{space 2} .0186798{col 40}{space 1}  -84.51{col 49}{space 3}0.000{col 57}{space 4}-1.615239{col 70}{space 3}-1.542015
{txt}{space 10}8040  {c |}{col 17}{res}{space 2}-1.797619{col 29}{space 2} .0301597{col 40}{space 1}  -59.60{col 49}{space 3}0.000{col 57}{space 4}-1.856731{col 70}{space 3}-1.738507
{txt}{space 10}8048  {c |}{col 17}{res}{space 2} -1.58962{col 29}{space 2} .0279077{col 40}{space 1}  -56.96{col 49}{space 3}0.000{col 57}{space 4}-1.644318{col 70}{space 3}-1.534922
{txt}{space 10}8056  {c |}{col 17}{res}{space 2}-1.616064{col 29}{space 2} .0301127{col 40}{space 1}  -53.67{col 49}{space 3}0.000{col 57}{space 4}-1.675084{col 70}{space 3}-1.557045
{txt}{space 10}8064  {c |}{col 17}{res}{space 2}-1.376633{col 29}{space 2} .0297018{col 40}{space 1}  -46.35{col 49}{space 3}0.000{col 57}{space 4}-1.434847{col 70}{space 3}-1.318418
{txt}{space 9}14014  {c |}{col 17}{res}{space 2}  -.23874{col 29}{space 2} .0186236{col 40}{space 1}  -12.82{col 49}{space 3}0.000{col 57}{space 4}-.2752416{col 70}{space 3}-.2022383
{txt}{space 9}14028  {c |}{col 17}{res}{space 2}-.5890087{col 29}{space 2} .0210781{col 40}{space 1}  -27.94{col 49}{space 3}0.000{col 57}{space 4} -.630321{col 70}{space 3}-.5476964
{txt}{space 9}14042  {c |}{col 17}{res}{space 2}-.7541887{col 29}{space 2} .0250335{col 40}{space 1}  -30.13{col 49}{space 3}0.000{col 57}{space 4}-.8032535{col 70}{space 3}-.7051239
{txt}{space 9}14056  {c |}{col 17}{res}{space 2}-.6164591{col 29}{space 2} .0323273{col 40}{space 1}  -19.07{col 49}{space 3}0.000{col 57}{space 4}-.6798193{col 70}{space 3}-.5530988
{txt}{space 9}14070  {c |}{col 17}{res}{space 2}-.7760352{col 29}{space 2} .0279311{col 40}{space 1}  -27.78{col 49}{space 3}0.000{col 57}{space 4}-.8307792{col 70}{space 3}-.7212913
{txt}{space 9}14084  {c |}{col 17}{res}{space 2}-.8199776{col 29}{space 2}  .036528{col 40}{space 1}  -22.45{col 49}{space 3}0.000{col 57}{space 4}-.8915712{col 70}{space 3} -.748384
{txt}{space 9}14098  {c |}{col 17}{res}{space 2}-.8479832{col 29}{space 2} .0468761{col 40}{space 1}  -18.09{col 49}{space 3}0.000{col 57}{space 4}-.9398586{col 70}{space 3}-.7561078
{txt}{space 9}14112  {c |}{col 17}{res}{space 2}-.6734942{col 29}{space 2} .0527157{col 40}{space 1}  -12.78{col 49}{space 3}0.000{col 57}{space 4} -.776815{col 70}{space 3}-.5701734
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{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .1301384{col 29}{space 2} .0492794{col 40}{space 1}    2.64{col 49}{space 3}0.008{col 57}{space 4} .0335525{col 70}{space 3} .2267244
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .3161669{col 29}{space 2} .0453891{col 40}{space 1}    6.97{col 49}{space 3}0.000{col 57}{space 4} .2272058{col 70}{space 3}  .405128
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-2.018328{col 29}{space 2} .3997916{col 40}{space 1}   -5.05{col 49}{space 3}0.000{col 57}{space 4}-2.801905{col 70}{space 3}-1.234751
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   105,715
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(voted), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0157727{col 29}{space 2} .0030829{col 40}{space 1}    5.12{col 49}{space 3}0.000{col 57}{space 4} .0097303{col 70}{space 3} .0218151
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0015573{col 29}{space 2} .0023933{col 40}{space 1}    0.65{col 49}{space 3}0.515{col 57}{space 4}-.0031335{col 70}{space 3} .0062481
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0059304{col 29}{space 2} .0005396{col 40}{space 1}   10.99{col 49}{space 3}0.000{col 57}{space 4} .0048728{col 70}{space 3}  .006988
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0119313{col 29}{space 2}  .001844{col 40}{space 1}    6.47{col 49}{space 3}0.000{col 57}{space 4} .0083172{col 70}{space 3} .0155454
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0450742{col 29}{space 2} .0090229{col 40}{space 1}    5.00{col 49}{space 3}0.000{col 57}{space 4} .0273895{col 70}{space 3} .0627588
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0462196{col 29}{space 2} .0153665{col 40}{space 1}   -3.01{col 49}{space 3}0.003{col 57}{space 4}-.0763374{col 70}{space 3}-.0161017
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2}-.0184716{col 29}{space 2} .0270263{col 40}{space 1}   -0.68{col 49}{space 3}0.494{col 57}{space 4}-.0714422{col 70}{space 3} .0344991
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0306945{col 29}{space 2} .0053093{col 40}{space 1}   -5.78{col 49}{space 3}0.000{col 57}{space 4}-.0411004{col 70}{space 3}-.0202885
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.0338465{col 29}{space 2} .0036035{col 40}{space 1}   -9.39{col 49}{space 3}0.000{col 57}{space 4}-.0409092{col 70}{space 3}-.0267839
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .0169437{col 29}{space 2} .0038034{col 40}{space 1}    4.45{col 49}{space 3}0.000{col 57}{space 4} .0094892{col 70}{space 3} .0243981
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2} .0307708{col 29}{space 2} .0013835{col 40}{space 1}   22.24{col 49}{space 3}0.000{col 57}{space 4} .0280592{col 70}{space 3} .0334824
{txt}{space 10}4012  {c |}{col 17}{res}{space 2} .0229555{col 29}{space 2} .0015262{col 40}{space 1}   15.04{col 49}{space 3}0.000{col 57}{space 4} .0199642{col 70}{space 3} .0259469
{txt}{space 10}4016  {c |}{col 17}{res}{space 2} .0202521{col 29}{space 2} .0010282{col 40}{space 1}   19.70{col 49}{space 3}0.000{col 57}{space 4} .0182368{col 70}{space 3} .0222674
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.0036045{col 29}{space 2} .0012556{col 40}{space 1}   -2.87{col 49}{space 3}0.004{col 57}{space 4}-.0060654{col 70}{space 3}-.0011436
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.0132561{col 29}{space 2} .0011382{col 40}{space 1}  -11.65{col 49}{space 3}0.000{col 57}{space 4} -.015487{col 70}{space 3}-.0110252
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.0118577{col 29}{space 2} .0013777{col 40}{space 1}   -8.61{col 49}{space 3}0.000{col 57}{space 4}-.0145579{col 70}{space 3}-.0091575
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store turnout1
{txt}
{com}. 
. coefplot interest1 , drop (_cons *.election) xline(0) rescale(100) levels(95 90) omitted baselevels headings(0.GL = "{c -(}bf:Sexuality{c )-}" 0.gender = "{c -(}bf:Sex{c )-}" 1.employ = "{c -(}bf:Employment{c )-}" 0.rural = "{c -(}bf:Rurality{c )-}") 
{res}{txt}
{com}. 
. 
. coefplot turnout1 , drop (_cons *.election) xline(0) rescale(100) levels(95 90) omitted baselevels headings(0.GL = "{c -(}bf:Sexuality{c )-}" 0.gender = "{c -(}bf:Sex{c )-}" 1.employ = "{c -(}bf:Employment{c )-}" 0.rural = "{c -(}bf:Rurality{c )-}") 
{res}{txt}
{com}. 
. 
. 
. 
. 
. //Figure 2//
. logit voted i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-55884.965}  
Iteration 1:{space 3}log pseudolikelihood = {res:-50526.931}  
Iteration 2:{space 3}log pseudolikelihood = {res:-50130.429}  
Iteration 3:{space 3}log pseudolikelihood = {res:-50128.446}  
Iteration 4:{space 3}log pseudolikelihood = {res:-50128.444}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   105,715
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-50128.444{txt}{col 49}Pseudo R2{col 67}= {res}    0.1030

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}          voted{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1260183{col 29}{space 2} .0252596{col 40}{space 1}    4.99{col 49}{space 3}0.000{col 57}{space 4} .0765105{col 70}{space 3} .1755262
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-2.018328{col 29}{space 2} .3997916{col 40}{space 1}   -5.05{col 49}{space 3}0.000{col 57}{space 4}-2.801905{col 70}{space 3}-1.234751
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   105,715
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(voted), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
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{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0157727{col 29}{space 2} .0030829{col 40}{space 1}    5.12{col 49}{space 3}0.000{col 57}{space 4} .0097303{col 70}{space 3} .0218151
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .0169437{col 29}{space 2} .0038034{col 40}{space 1}    4.45{col 49}{space 3}0.000{col 57}{space 4} .0094892{col 70}{space 3} .0243981
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 9}52052  {c |}{col 17}{res}{space 2}-.0276369{col 29}{space 2} .0121473{col 40}{space 1}   -2.28{col 49}{space 3}0.023{col 57}{space 4}-.0514452{col 70}{space 3}-.0038285
{txt}{space 9}52104  {c |}{col 17}{res}{space 2}-.0513674{col 29}{space 2}  .014206{col 40}{space 1}   -3.62{col 49}{space 3}0.000{col 57}{space 4}-.0792106{col 70}{space 3}-.0235242
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{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .0092166{col 29}{space 2} .0033297{col 40}{space 1}    2.77{col 49}{space 3}0.006{col 57}{space 4} .0026905{col 70}{space 3} .0157427
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .0208714{col 29}{space 2} .0027019{col 40}{space 1}    7.72{col 49}{space 3}0.000{col 57}{space 4} .0155757{col 70}{space 3}  .026167
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store full1
{txt}
{com}. 
. logit voted i.GL i.gender agea eduyrs swi i.employ i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-55884.965}  
Iteration 1:{space 3}log pseudolikelihood = {res:-50554.119}  
Iteration 2:{space 3}log pseudolikelihood = {res:-50160.677}  
Iteration 3:{space 3}log pseudolikelihood = {res:-50158.745}  
Iteration 4:{space 3}log pseudolikelihood = {res:-50158.743}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   105,715
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(9)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-50158.743{txt}{col 49}Pseudo R2{col 67}= {res}    0.1025

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}          voted{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2}  .121611{col 29}{space 2} .0238079{col 40}{space 1}    5.11{col 49}{space 3}0.000{col 57}{space 4} .0749485{col 70}{space 3} .1682736
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0459574{col 29}{space 2} .0046007{col 40}{space 1}    9.99{col 49}{space 3}0.000{col 57}{space 4} .0369403{col 70}{space 3} .0549746
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0909268{col 29}{space 2} .0151338{col 40}{space 1}    6.01{col 49}{space 3}0.000{col 57}{space 4} .0612651{col 70}{space 3} .1205884
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .3486298{col 29}{space 2} .0710177{col 40}{space 1}    4.91{col 49}{space 3}0.000{col 57}{space 4} .2094377{col 70}{space 3} .4878219
{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{space 6}Studying  {c |}{col 17}{res}{space 2}-.1612725{col 29}{space 2} .1979405{col 40}{space 1}   -0.81{col 49}{space 3}0.415{col 57}{space 4}-.5492287{col 70}{space 3} .2266837
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.2363114{col 29}{space 2} .0405073{col 40}{space 1}   -5.83{col 49}{space 3}0.000{col 57}{space 4}-.3157042{col 70}{space 3}-.1569186
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.2617214{col 29}{space 2} .0264809{col 40}{space 1}   -9.88{col 49}{space 3}0.000{col 57}{space 4} -.313623{col 70}{space 3}-.2098197
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-1.936781{col 29}{space 2} .3891685{col 40}{space 1}   -4.98{col 49}{space 3}0.000{col 57}{space 4}-2.699537{col 70}{space 3}-1.174025
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   105,715
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(voted), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0152507{col 29}{space 2} .0029221{col 40}{space 1}    5.22{col 49}{space 3}0.000{col 57}{space 4} .0095235{col 70}{space 3} .0209779
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0012608{col 29}{space 2} .0024022{col 40}{space 1}    0.52{col 49}{space 3}0.600{col 57}{space 4}-.0034475{col 70}{space 3} .0059691
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{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0451584{col 29}{space 2} .0090461{col 40}{space 1}    4.99{col 49}{space 3}0.000{col 57}{space 4} .0274283{col 70}{space 3} .0628885
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0475862{col 29}{space 2} .0157501{col 40}{space 1}   -3.02{col 49}{space 3}0.003{col 57}{space 4}-.0784559{col 70}{space 3}-.0167165
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{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0308711{col 29}{space 2}  .005374{col 40}{space 1}   -5.74{col 49}{space 3}0.000{col 57}{space 4} -.041404{col 70}{space 3}-.0203383
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.0344221{col 29}{space 2} .0037195{col 40}{space 1}   -9.25{col 49}{space 3}0.000{col 57}{space 4}-.0417123{col 70}{space 3} -.027132
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2} .0299904{col 29}{space 2} .0011977{col 40}{space 1}   25.04{col 49}{space 3}0.000{col 57}{space 4} .0276429{col 70}{space 3} .0323379
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{txt}{space 9}14098  {c |}{col 17}{res}{space 2}-.0874914{col 29}{space 2} .0050455{col 40}{space 1}  -17.34{col 49}{space 3}0.000{col 57}{space 4}-.0973803{col 70}{space 3}-.0776025
{txt}{space 9}14112  {c |}{col 17}{res}{space 2}-.0654948{col 29}{space 2} .0056745{col 40}{space 1}  -11.54{col 49}{space 3}0.000{col 57}{space 4}-.0766166{col 70}{space 3} -.054373
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{txt}{space 9}20060  {c |}{col 17}{res}{space 2}-.0683111{col 29}{space 2}  .003767{col 40}{space 1}  -18.13{col 49}{space 3}0.000{col 57}{space 4}-.0756942{col 70}{space 3} -.060928
{txt}{space 9}20080  {c |}{col 17}{res}{space 2} -.035247{col 29}{space 2}  .004471{col 40}{space 1}   -7.88{col 49}{space 3}0.000{col 57}{space 4}-.0440099{col 70}{space 3}-.0264841
{txt}{space 9}20100  {c |}{col 17}{res}{space 2}-.0242968{col 29}{space 2} .0043894{col 40}{space 1}   -5.54{col 49}{space 3}0.000{col 57}{space 4}-.0328998{col 70}{space 3}-.0156937
{txt}{space 9}20120  {c |}{col 17}{res}{space 2}-.0747362{col 29}{space 2} .0079118{col 40}{space 1}   -9.45{col 49}{space 3}0.000{col 57}{space 4}-.0902431{col 70}{space 3}-.0592293
{txt}{space 9}20140  {c |}{col 17}{res}{space 2}-.0720269{col 29}{space 2} .0054941{col 40}{space 1}  -13.11{col 49}{space 3}0.000{col 57}{space 4}-.0827952{col 70}{space 3}-.0612585
{txt}{space 9}20160  {c |}{col 17}{res}{space 2}-.0234231{col 29}{space 2} .0045323{col 40}{space 1}   -5.17{col 49}{space 3}0.000{col 57}{space 4}-.0323063{col 70}{space 3}  -.01454
{txt}{space 9}22022  {c |}{col 17}{res}{space 2}-.0578107{col 29}{space 2} .0005767{col 40}{space 1} -100.24{col 49}{space 3}0.000{col 57}{space 4}-.0589411{col 70}{space 3}-.0566803
{txt}{space 9}22044  {c |}{col 17}{res}{space 2}-.0823313{col 29}{space 2} .0010707{col 40}{space 1}  -76.90{col 49}{space 3}0.000{col 57}{space 4}-.0844298{col 70}{space 3}-.0802328
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{txt}{space 9}48384  {c |}{col 17}{res}{space 2}-.0291118{col 29}{space 2} .0058906{col 40}{space 1}   -4.94{col 49}{space 3}0.000{col 57}{space 4}-.0406572{col 70}{space 3}-.0175664
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{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .0071797{col 29}{space 2} .0036469{col 40}{space 1}    1.97{col 49}{space 3}0.049{col 57}{space 4} .0000319{col 70}{space 3} .0143275
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .0188154{col 29}{space 2} .0029786{col 40}{space 1}    6.32{col 49}{space 3}0.000{col 57}{space 4} .0129776{col 70}{space 3} .0246533
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store nourban1
{txt}
{com}. 
. logit voted i.GL i.gender agea eduyrs swi i.employ i.election if fulldata==1 & partner==1 & rural==0 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-34826.488}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31028.252}  
Iteration 2:{space 3}log pseudolikelihood = {res:-30731.139}  
Iteration 3:{space 3}log pseudolikelihood = {res:-30729.484}  
Iteration 4:{space 3}log pseudolikelihood = {res:-30729.479}  
Iteration 5:{space 3}log pseudolikelihood = {res:-30729.479}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}    60,897
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(8)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-30729.479{txt}{col 49}Pseudo R2{col 67}= {res}    0.1176

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}          voted{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .2154424{col 29}{space 2} .0488555{col 40}{space 1}    4.41{col 49}{space 3}0.000{col 57}{space 4} .1196873{col 70}{space 3} .3111975
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0223563{col 29}{space 2} .0332504{col 40}{space 1}    0.67{col 49}{space 3}0.501{col 57}{space 4}-.0428133{col 70}{space 3} .0875259
{txt}{space 11}agea {c |}{col 17}{res}{space 2}  .047691{col 29}{space 2} .0047001{col 40}{space 1}   10.15{col 49}{space 3}0.000{col 57}{space 4} .0384791{col 70}{space 3}  .056903
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0980543{col 29}{space 2} .0140046{col 40}{space 1}    7.00{col 49}{space 3}0.000{col 57}{space 4} .0706057{col 70}{space 3} .1255028
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .3801073{col 29}{space 2} .0728807{col 40}{space 1}    5.22{col 49}{space 3}0.000{col 57}{space 4} .2372637{col 70}{space 3} .5229509
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.4684611{col 29}{space 2} .1069004{col 40}{space 1}   -4.38{col 49}{space 3}0.000{col 57}{space 4}-.6779819{col 70}{space 3}-.2589402
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2}-.1062262{col 29}{space 2} .2530012{col 40}{space 1}   -0.42{col 49}{space 3}0.675{col 57}{space 4}-.6020994{col 70}{space 3}  .389647
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.3123649{col 29}{space 2} .0380856{col 40}{space 1}   -8.20{col 49}{space 3}0.000{col 57}{space 4}-.3870112{col 70}{space 3}-.2377185
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.2881003{col 29}{space 2} .0243013{col 40}{space 1}  -11.86{col 49}{space 3}0.000{col 57}{space 4}  -.33573{col 70}{space 3}-.2404707
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2} .3190274{col 29}{space 2} .0261603{col 40}{space 1}   12.20{col 49}{space 3}0.000{col 57}{space 4} .2677541{col 70}{space 3} .3703007
{txt}{space 10}4012  {c |}{col 17}{res}{space 2} .2898138{col 29}{space 2} .0287231{col 40}{space 1}   10.09{col 49}{space 3}0.000{col 57}{space 4} .2335176{col 70}{space 3}   .34611
{txt}{space 10}4016  {c |}{col 17}{res}{space 2} .2322659{col 29}{space 2} .0158217{col 40}{space 1}   14.68{col 49}{space 3}0.000{col 57}{space 4} .2012559{col 70}{space 3} .2632759
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{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.0896436{col 29}{space 2} .0163767{col 40}{space 1}   -5.47{col 49}{space 3}0.000{col 57}{space 4}-.1217413{col 70}{space 3}-.0575459
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.2603143{col 29}{space 2} .0151949{col 40}{space 1}  -17.13{col 49}{space 3}0.000{col 57}{space 4}-.2900958{col 70}{space 3}-.2305328
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{txt}{space 10}8008  {c |}{col 17}{res}{space 2}-1.294833{col 29}{space 2} .0221423{col 40}{space 1}  -58.48{col 49}{space 3}0.000{col 57}{space 4}-1.338231{col 70}{space 3}-1.251435
{txt}{space 10}8016  {c |}{col 17}{res}{space 2} -1.35175{col 29}{space 2} .0153665{col 40}{space 1}  -87.97{col 49}{space 3}0.000{col 57}{space 4}-1.381868{col 70}{space 3}-1.321633
{txt}{space 10}8024  {c |}{col 17}{res}{space 2}-1.668093{col 29}{space 2} .0522978{col 40}{space 1}  -31.90{col 49}{space 3}0.000{col 57}{space 4}-1.770595{col 70}{space 3}-1.565592
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{txt}{space 9}14112  {c |}{col 17}{res}{space 2}-.7137416{col 29}{space 2} .0577554{col 40}{space 1}  -12.36{col 49}{space 3}0.000{col 57}{space 4}  -.82694{col 70}{space 3}-.6005431
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{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .3626179{col 29}{space 2}  .064316{col 40}{space 1}    5.64{col 49}{space 3}0.000{col 57}{space 4} .2365609{col 70}{space 3}  .488675
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-2.294882{col 29}{space 2} .4021911{col 40}{space 1}   -5.71{col 49}{space 3}0.000{col 57}{space 4}-3.083162{col 70}{space 3}-1.506602
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    60,897
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(voted), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2}  .026778{col 29}{space 2} .0056232{col 40}{space 1}    4.76{col 49}{space 3}0.000{col 57}{space 4} .0157568{col 70}{space 3} .0377992
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0029352{col 29}{space 2} .0043431{col 40}{space 1}    0.68{col 49}{space 3}0.499{col 57}{space 4}-.0055771{col 70}{space 3} .0114475
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0062615{col 29}{space 2} .0005663{col 40}{space 1}   11.06{col 49}{space 3}0.000{col 57}{space 4} .0051516{col 70}{space 3} .0073714
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0128739{col 29}{space 2} .0017096{col 40}{space 1}    7.53{col 49}{space 3}0.000{col 57}{space 4} .0095232{col 70}{space 3} .0162245
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0499055{col 29}{space 2} .0093127{col 40}{space 1}    5.36{col 49}{space 3}0.000{col 57}{space 4} .0316529{col 70}{space 3} .0681581
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0650959{col 29}{space 2} .0164664{col 40}{space 1}   -3.95{col 49}{space 3}0.000{col 57}{space 4}-.0973694{col 70}{space 3}-.0328223
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2}-.0134759{col 29}{space 2} .0330441{col 40}{space 1}   -0.41{col 49}{space 3}0.683{col 57}{space 4}-.0782412{col 70}{space 3} .0512895
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0417826{col 29}{space 2} .0051733{col 40}{space 1}   -8.08{col 49}{space 3}0.000{col 57}{space 4}-.0519221{col 70}{space 3}-.0316431
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.0383032{col 29}{space 2} .0031304{col 40}{space 1}  -12.24{col 49}{space 3}0.000{col 57}{space 4}-.0444387{col 70}{space 3}-.0321677
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2} .0222841{col 29}{space 2} .0016218{col 40}{space 1}   13.74{col 49}{space 3}0.000{col 57}{space 4} .0191054{col 70}{space 3} .0254628
{txt}{space 10}4012  {c |}{col 17}{res}{space 2} .0204601{col 29}{space 2} .0018844{col 40}{space 1}   10.86{col 49}{space 3}0.000{col 57}{space 4} .0167669{col 70}{space 3} .0241534
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{txt}{space 10}4020  {c |}{col 17}{res}{space 2} .0015338{col 29}{space 2} .0019984{col 40}{space 1}    0.77{col 49}{space 3}0.443{col 57}{space 4}-.0023829{col 70}{space 3} .0054505
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.0072618{col 29}{space 2} .0013041{col 40}{space 1}   -5.57{col 49}{space 3}0.000{col 57}{space 4}-.0098177{col 70}{space 3}-.0047059
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.0224127{col 29}{space 2} .0011094{col 40}{space 1}  -20.20{col 49}{space 3}0.000{col 57}{space 4}-.0245871{col 70}{space 3}-.0202383
{txt}{space 10}4032  {c |}{col 17}{res}{space 2}-.0140327{col 29}{space 2} .0017103{col 40}{space 1}   -8.20{col 49}{space 3}0.000{col 57}{space 4}-.0173849{col 70}{space 3}-.0106805
{txt}{space 10}8008  {c |}{col 17}{res}{space 2}-.1563538{col 29}{space 2} .0027184{col 40}{space 1}  -57.52{col 49}{space 3}0.000{col 57}{space 4}-.1616818{col 70}{space 3}-.1510258
{txt}{space 10}8016  {c |}{col 17}{res}{space 2} -.165909{col 29}{space 2} .0027246{col 40}{space 1}  -60.89{col 49}{space 3}0.000{col 57}{space 4}-.1712491{col 70}{space 3}-.1605688
{txt}{space 10}8024  {c |}{col 17}{res}{space 2}-.2228383{col 29}{space 2} .0051191{col 40}{space 1}  -43.53{col 49}{space 3}0.000{col 57}{space 4}-.2328715{col 70}{space 3} -.212805
{txt}{space 10}8032  {c |}{col 17}{res}{space 2}-.1706637{col 29}{space 2} .0021987{col 40}{space 1}  -77.62{col 49}{space 3}0.000{col 57}{space 4}-.1749732{col 70}{space 3}-.1663543
{txt}{space 10}8040  {c |}{col 17}{res}{space 2}-.2671091{col 29}{space 2} .0014509{col 40}{space 1} -184.09{col 49}{space 3}0.000{col 57}{space 4}-.2699529{col 70}{space 3}-.2642654
{txt}{space 10}8048  {c |}{col 17}{res}{space 2}-.2152178{col 29}{space 2} .0031076{col 40}{space 1}  -69.26{col 49}{space 3}0.000{col 57}{space 4}-.2213086{col 70}{space 3}-.2091271
{txt}{space 10}8056  {c |}{col 17}{res}{space 2}-.1925029{col 29}{space 2}  .002659{col 40}{space 1}  -72.40{col 49}{space 3}0.000{col 57}{space 4}-.1977145{col 70}{space 3}-.1872913
{txt}{space 10}8064  {c |}{col 17}{res}{space 2}-.1550927{col 29}{space 2} .0014424{col 40}{space 1} -107.52{col 49}{space 3}0.000{col 57}{space 4}-.1579198{col 70}{space 3}-.1522656
{txt}{space 9}14014  {c |}{col 17}{res}{space 2}-.0190394{col 29}{space 2} .0015098{col 40}{space 1}  -12.61{col 49}{space 3}0.000{col 57}{space 4}-.0219986{col 70}{space 3}-.0160802
{txt}{space 9}14028  {c |}{col 17}{res}{space 2}-.0526159{col 29}{space 2} .0017957{col 40}{space 1}  -29.30{col 49}{space 3}0.000{col 57}{space 4}-.0561354{col 70}{space 3}-.0490965
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{txt}{space 9}56168  {c |}{col 17}{res}{space 2} .0179257{col 29}{space 2} .0039371{col 40}{space 1}    4.55{col 49}{space 3}0.000{col 57}{space 4} .0102091{col 70}{space 3} .0256422
{txt}{space 9}56224  {c |}{col 17}{res}{space 2} .0220674{col 29}{space 2} .0033789{col 40}{space 1}    6.53{col 49}{space 3}0.000{col 57}{space 4} .0154449{col 70}{space 3}   .02869
{txt}{space 9}56280  {c |}{col 17}{res}{space 2} .0500391{col 29}{space 2}  .002717{col 40}{space 1}   18.42{col 49}{space 3}0.000{col 57}{space 4} .0447139{col 70}{space 3} .0553642
{txt}{space 9}56336  {c |}{col 17}{res}{space 2} .0079393{col 29}{space 2} .0033586{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} .0013565{col 70}{space 3} .0145221
{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .0120198{col 29}{space 2}  .004939{col 40}{space 1}    2.43{col 49}{space 3}0.015{col 57}{space 4} .0023396{col 70}{space 3} .0217001
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .0249297{col 29}{space 2} .0040722{col 40}{space 1}    6.12{col 49}{space 3}0.000{col 57}{space 4} .0169483{col 70}{space 3} .0329111
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store urban1
{txt}
{com}. 
. logit interested i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-87167.942}  
Iteration 1:{space 3}log pseudolikelihood = {res:-75709.179}  
Iteration 2:{space 3}log pseudolikelihood = {res:-75634.005}  
Iteration 3:{space 3}log pseudolikelihood = {res:-75633.892}  
Iteration 4:{space 3}log pseudolikelihood = {res:-75633.892}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,726
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(9)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-75633.892{txt}{col 49}Pseudo R2{col 67}= {res}    0.1323

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}     interested{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1276096{col 29}{space 2} .0220308{col 40}{space 1}    5.79{col 49}{space 3}0.000{col 57}{space 4}   .08443{col 70}{space 3} .1707893
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .6020354{col 29}{space 2}  .025027{col 40}{space 1}   24.06{col 49}{space 3}0.000{col 57}{space 4} .5529834{col 70}{space 3} .6510874
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0254423{col 29}{space 2} .0039331{col 40}{space 1}    6.47{col 49}{space 3}0.000{col 57}{space 4} .0177335{col 70}{space 3} .0331511
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .1514151{col 29}{space 2}  .012987{col 40}{space 1}   11.66{col 49}{space 3}0.000{col 57}{space 4} .1259609{col 70}{space 3} .1768692
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .2345643{col 29}{space 2} .0306337{col 40}{space 1}    7.66{col 49}{space 3}0.000{col 57}{space 4} .1745233{col 70}{space 3} .2946053
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0257435{col 29}{space 2} .0477422{col 40}{space 1}    0.54{col 49}{space 3}0.590{col 57}{space 4}-.0678294{col 70}{space 3} .1193165
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .3837853{col 29}{space 2} .0498282{col 40}{space 1}    7.70{col 49}{space 3}0.000{col 57}{space 4} .2861239{col 70}{space 3} .4814467
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0707536{col 29}{space 2} .0309065{col 40}{space 1}   -2.29{col 49}{space 3}0.022{col 57}{space 4}-.1313293{col 70}{space 3}-.0101779
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} .0362094{col 29}{space 2} .0521798{col 40}{space 1}    0.69{col 49}{space 3}0.488{col 57}{space 4} -.066061{col 70}{space 3} .1384799
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.1424878{col 29}{space 2} .0596173{col 40}{space 1}   -2.39{col 49}{space 3}0.017{col 57}{space 4}-.2593355{col 70}{space 3}-.0256401
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.1054236{col 29}{space 2} .0061806{col 40}{space 1}  -17.06{col 49}{space 3}0.000{col 57}{space 4}-.1175374{col 70}{space 3}-.0933099
{txt}{space 10}4012  {c |}{col 17}{res}{space 2}-.0716038{col 29}{space 2} .0137515{col 40}{space 1}   -5.21{col 49}{space 3}0.000{col 57}{space 4}-.0985563{col 70}{space 3}-.0446513
{txt}{space 10}4016  {c |}{col 17}{res}{space 2} .1019792{col 29}{space 2}  .014326{col 40}{space 1}    7.12{col 49}{space 3}0.000{col 57}{space 4} .0739007{col 70}{space 3} .1300578
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.0425561{col 29}{space 2} .0162804{col 40}{space 1}   -2.61{col 49}{space 3}0.009{col 57}{space 4} -.074465{col 70}{space 3}-.0106471
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.0989132{col 29}{space 2} .0209164{col 40}{space 1}   -4.73{col 49}{space 3}0.000{col 57}{space 4}-.1399086{col 70}{space 3}-.0579178
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} -4.16282{col 29}{space 2} .4328785{col 40}{space 1}   -9.62{col 49}{space 3}0.000{col 57}{space 4}-5.011247{col 70}{space 3}-3.314394
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,726
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(interested), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0261504{col 29}{space 2} .0044228{col 40}{space 1}    5.91{col 49}{space 3}0.000{col 57}{space 4} .0174819{col 70}{space 3} .0348189
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store full2
{txt}
{com}. 
. logit interested i.GL i.gender agea eduyrs swi i.employ i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-87167.942}  
Iteration 1:{space 3}log pseudolikelihood = {res:-75767.706}  
Iteration 2:{space 3}log pseudolikelihood = {res:-75694.166}  
Iteration 3:{space 3}log pseudolikelihood = {res:-75694.059}  
Iteration 4:{space 3}log pseudolikelihood = {res:-75694.059}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,726
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(8)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-75694.059{txt}{col 49}Pseudo R2{col 67}= {res}    0.1316

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}     interested{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1327898{col 29}{space 2} .0225793{col 40}{space 1}    5.88{col 49}{space 3}0.000{col 57}{space 4} .0885353{col 70}{space 3} .1770444
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{space 12}swi {c |}{col 17}{res}{space 2} .2338752{col 29}{space 2} .0307923{col 40}{space 1}    7.60{col 49}{space 3}0.000{col 57}{space 4} .1735233{col 70}{space 3}  .294227
{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}  -4.2546{col 29}{space 2} .4078858{col 40}{space 1}  -10.43{col 49}{space 3}0.000{col 57}{space 4}-5.054042{col 70}{space 3}-3.455159
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,726
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(interested), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0272315{col 29}{space 2} .0045097{col 40}{space 1}    6.04{col 49}{space 3}0.000{col 57}{space 4} .0183926{col 70}{space 3} .0360704
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store nourban2
{txt}
{com}. 
. logit interested i.GL i.gender agea eduyrs swi i.employ i.election if fulldata==1 & partner==1 & rural==0 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-52940.444}  
Iteration 1:{space 3}log pseudolikelihood = {res:-46414.528}  
Iteration 2:{space 3}log pseudolikelihood = {res:-46365.632}  
Iteration 3:{space 3}log pseudolikelihood = {res:-46365.567}  
Iteration 4:{space 3}log pseudolikelihood = {res:-46365.567}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}    64,201
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(8)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-46365.567{txt}{col 49}Pseudo R2{col 67}= {res}    0.1242

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}     interested{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .2168813{col 29}{space 2} .0562929{col 40}{space 1}    3.85{col 49}{space 3}0.000{col 57}{space 4} .1065492{col 70}{space 3} .3272133
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .5950507{col 29}{space 2} .0131397{col 40}{space 1}   45.29{col 49}{space 3}0.000{col 57}{space 4} .5692973{col 70}{space 3} .6208041
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0255607{col 29}{space 2} .0041827{col 40}{space 1}    6.11{col 49}{space 3}0.000{col 57}{space 4} .0173627{col 70}{space 3} .0337586
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .1521489{col 29}{space 2} .0152343{col 40}{space 1}    9.99{col 49}{space 3}0.000{col 57}{space 4} .1222902{col 70}{space 3} .1820075
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .2207962{col 29}{space 2}  .031178{col 40}{space 1}    7.08{col 49}{space 3}0.000{col 57}{space 4} .1596885{col 70}{space 3} .2819039
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0277803{col 29}{space 2} .0778307{col 40}{space 1}    0.36{col 49}{space 3}0.721{col 57}{space 4} -.124765{col 70}{space 3} .1803256
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .3573627{col 29}{space 2}  .075606{col 40}{space 1}    4.73{col 49}{space 3}0.000{col 57}{space 4} .2091776{col 70}{space 3} .5055478
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0856177{col 29}{space 2}  .037629{col 40}{space 1}   -2.28{col 49}{space 3}0.023{col 57}{space 4}-.1593692{col 70}{space 3}-.0118661
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} .0546425{col 29}{space 2} .0536815{col 40}{space 1}    1.02{col 49}{space 3}0.309{col 57}{space 4}-.0505713{col 70}{space 3} .1598562
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 9}52104  {c |}{col 17}{res}{space 2} .0821959{col 29}{space 2} .0613445{col 40}{space 1}    1.34{col 49}{space 3}0.180{col 57}{space 4} -.038037{col 70}{space 3} .2024289
{txt}{space 9}52156  {c |}{col 17}{res}{space 2}-.0217336{col 29}{space 2} .0476402{col 40}{space 1}   -0.46{col 49}{space 3}0.648{col 57}{space 4}-.1151066{col 70}{space 3} .0716395
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{txt}{space 9}56168  {c |}{col 17}{res}{space 2} .5211711{col 29}{space 2}  .015432{col 40}{space 1}   33.77{col 49}{space 3}0.000{col 57}{space 4} .4909249{col 70}{space 3} .5514173
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{txt}{space 9}56280  {c |}{col 17}{res}{space 2} .3732677{col 29}{space 2} .0261337{col 40}{space 1}   14.28{col 49}{space 3}0.000{col 57}{space 4} .3220466{col 70}{space 3} .4244888
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{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .6164852{col 29}{space 2} .0367287{col 40}{space 1}   16.78{col 49}{space 3}0.000{col 57}{space 4} .5444982{col 70}{space 3} .6884721
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .4176083{col 29}{space 2} .0453203{col 40}{space 1}    9.21{col 49}{space 3}0.000{col 57}{space 4} .3287822{col 70}{space 3} .5064343
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-4.092179{col 29}{space 2} .4574471{col 40}{space 1}   -8.95{col 49}{space 3}0.000{col 57}{space 4}-4.988759{col 70}{space 3}-3.195599
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    64,201
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(interested), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0441422{col 29}{space 2} .0113167{col 40}{space 1}    3.90{col 49}{space 3}0.000{col 57}{space 4} .0219618{col 70}{space 3} .0663225
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .1246738{col 29}{space 2} .0021234{col 40}{space 1}   58.71{col 49}{space 3}0.000{col 57}{space 4} .1205121{col 70}{space 3} .1288355
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0052723{col 29}{space 2} .0007817{col 40}{space 1}    6.74{col 49}{space 3}0.000{col 57}{space 4} .0037402{col 70}{space 3} .0068043
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0313829{col 29}{space 2} .0025904{col 40}{space 1}   12.11{col 49}{space 3}0.000{col 57}{space 4} .0263057{col 70}{space 3} .0364601
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0455424{col 29}{space 2}  .005849{col 40}{space 1}    7.79{col 49}{space 3}0.000{col 57}{space 4} .0340786{col 70}{space 3} .0570063
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0057433{col 29}{space 2} .0159786{col 40}{space 1}    0.36{col 49}{space 3}0.719{col 57}{space 4}-.0255741{col 70}{space 3} .0370607
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .0721155{col 29}{space 2} .0139237{col 40}{space 1}    5.18{col 49}{space 3}0.000{col 57}{space 4} .0448255{col 70}{space 3} .0994055
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0178022{col 29}{space 2} .0079886{col 40}{space 1}   -2.23{col 49}{space 3}0.026{col 57}{space 4}-.0334596{col 70}{space 3}-.0021448
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} .0112792{col 29}{space 2} .0109796{col 40}{space 1}    1.03{col 49}{space 3}0.304{col 57}{space 4}-.0102404{col 70}{space 3} .0327989
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.0496521{col 29}{space 2} .0018046{col 40}{space 1}  -27.51{col 49}{space 3}0.000{col 57}{space 4} -.053189{col 70}{space 3}-.0461152
{txt}{space 10}4012  {c |}{col 17}{res}{space 2}-.0054387{col 29}{space 2} .0027693{col 40}{space 1}   -1.96{col 49}{space 3}0.050{col 57}{space 4}-.0108665{col 70}{space 3}-.0000109
{txt}{space 10}4016  {c |}{col 17}{res}{space 2}   .00707{col 29}{space 2} .0036941{col 40}{space 1}    1.91{col 49}{space 3}0.056{col 57}{space 4}-.0001703{col 70}{space 3} .0143103
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.0107874{col 29}{space 2} .0035703{col 40}{space 1}   -3.02{col 49}{space 3}0.003{col 57}{space 4}-.0177852{col 70}{space 3}-.0037897
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.0117534{col 29}{space 2} .0042644{col 40}{space 1}   -2.76{col 49}{space 3}0.006{col 57}{space 4}-.0201115{col 70}{space 3}-.0033953
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.0278376{col 29}{space 2} .0050744{col 40}{space 1}   -5.49{col 49}{space 3}0.000{col 57}{space 4}-.0377831{col 70}{space 3} -.017892
{txt}{space 10}4032  {c |}{col 17}{res}{space 2}-.0878184{col 29}{space 2} .0064909{col 40}{space 1}  -13.53{col 49}{space 3}0.000{col 57}{space 4}-.1005404{col 70}{space 3}-.0750964
{txt}{space 10}8008  {c |}{col 17}{res}{space 2} .1597937{col 29}{space 2} .0017917{col 40}{space 1}   89.18{col 49}{space 3}0.000{col 57}{space 4} .1562819{col 70}{space 3} .1633054
{txt}{space 10}8016  {c |}{col 17}{res}{space 2} .1697446{col 29}{space 2} .0015407{col 40}{space 1}  110.17{col 49}{space 3}0.000{col 57}{space 4} .1667249{col 70}{space 3} .1727644
{txt}{space 10}8024  {c |}{col 17}{res}{space 2} .0603944{col 29}{space 2} .0071944{col 40}{space 1}    8.39{col 49}{space 3}0.000{col 57}{space 4} .0462937{col 70}{space 3}  .074495
{txt}{space 10}8032  {c |}{col 17}{res}{space 2} .0935513{col 29}{space 2} .0013539{col 40}{space 1}   69.10{col 49}{space 3}0.000{col 57}{space 4} .0908977{col 70}{space 3} .0962049
{txt}{space 10}8040  {c |}{col 17}{res}{space 2} .0815245{col 29}{space 2} .0031537{col 40}{space 1}   25.85{col 49}{space 3}0.000{col 57}{space 4} .0753434{col 70}{space 3} .0877056
{txt}{space 10}8048  {c |}{col 17}{res}{space 2} .1175693{col 29}{space 2} .0039403{col 40}{space 1}   29.84{col 49}{space 3}0.000{col 57}{space 4} .1098464{col 70}{space 3} .1252921
{txt}{space 10}8056  {c |}{col 17}{res}{space 2} .1003362{col 29}{space 2} .0034683{col 40}{space 1}   28.93{col 49}{space 3}0.000{col 57}{space 4} .0935384{col 70}{space 3} .1071339
{txt}{space 10}8064  {c |}{col 17}{res}{space 2}  .074298{col 29}{space 2} .0026055{col 40}{space 1}   28.52{col 49}{space 3}0.000{col 57}{space 4} .0691913{col 70}{space 3} .0794047
{txt}{space 9}14014  {c |}{col 17}{res}{space 2} .1426454{col 29}{space 2} .0055377{col 40}{space 1}   25.76{col 49}{space 3}0.000{col 57}{space 4} .1317916{col 70}{space 3} .1534991
{txt}{space 9}14028  {c |}{col 17}{res}{space 2} .0967303{col 29}{space 2} .0057116{col 40}{space 1}   16.94{col 49}{space 3}0.000{col 57}{space 4} .0855358{col 70}{space 3} .1079249
{txt}{space 9}14042  {c |}{col 17}{res}{space 2} .0407742{col 29}{space 2} .0060809{col 40}{space 1}    6.71{col 49}{space 3}0.000{col 57}{space 4} .0288559{col 70}{space 3} .0526925
{txt}{space 9}14056  {c |}{col 17}{res}{space 2} .0826571{col 29}{space 2}  .008252{col 40}{space 1}   10.02{col 49}{space 3}0.000{col 57}{space 4} .0664835{col 70}{space 3} .0988307
{txt}{space 9}14070  {c |}{col 17}{res}{space 2} .0775431{col 29}{space 2} .0067579{col 40}{space 1}   11.47{col 49}{space 3}0.000{col 57}{space 4} .0642979{col 70}{space 3} .0907883
{txt}{space 9}14084  {c |}{col 17}{res}{space 2} .0994689{col 29}{space 2} .0088935{col 40}{space 1}   11.18{col 49}{space 3}0.000{col 57}{space 4}  .082038{col 70}{space 3} .1168998
{txt}{space 9}14098  {c |}{col 17}{res}{space 2}  .103694{col 29}{space 2} .0108721{col 40}{space 1}    9.54{col 49}{space 3}0.000{col 57}{space 4} .0823851{col 70}{space 3} .1250028
{txt}{space 9}14112  {c |}{col 17}{res}{space 2} .1195924{col 29}{space 2} .0111426{col 40}{space 1}   10.73{col 49}{space 3}0.000{col 57}{space 4} .0977533{col 70}{space 3} .1414315
{txt}{space 9}20020  {c |}{col 17}{res}{space 2}-.1793958{col 29}{space 2} .0026344{col 40}{space 1}  -68.10{col 49}{space 3}0.000{col 57}{space 4}-.1845592{col 70}{space 3}-.1742324
{txt}{space 9}20040  {c |}{col 17}{res}{space 2}-.0942685{col 29}{space 2} .0009054{col 40}{space 1} -104.12{col 49}{space 3}0.000{col 57}{space 4} -.096043{col 70}{space 3}-.0924939
{txt}{space 9}20060  {c |}{col 17}{res}{space 2}-.1864522{col 29}{space 2} .0013346{col 40}{space 1} -139.71{col 49}{space 3}0.000{col 57}{space 4}-.1890679{col 70}{space 3}-.1838366
{txt}{space 9}20080  {c |}{col 17}{res}{space 2}-.1538329{col 29}{space 2} .0011531{col 40}{space 1} -133.41{col 49}{space 3}0.000{col 57}{space 4}-.1560929{col 70}{space 3}-.1515729
{txt}{space 9}20100  {c |}{col 17}{res}{space 2}-.1895226{col 29}{space 2} .0040294{col 40}{space 1}  -47.03{col 49}{space 3}0.000{col 57}{space 4}-.1974202{col 70}{space 3} -.181625
{txt}{space 9}20120  {c |}{col 17}{res}{space 2}-.0965572{col 29}{space 2}  .004571{col 40}{space 1}  -21.12{col 49}{space 3}0.000{col 57}{space 4}-.1055162{col 70}{space 3}-.0875983
{txt}{space 9}20140  {c |}{col 17}{res}{space 2}-.0481939{col 29}{space 2} .0053891{col 40}{space 1}   -8.94{col 49}{space 3}0.000{col 57}{space 4}-.0587563{col 70}{space 3}-.0376315
{txt}{space 9}20160  {c |}{col 17}{res}{space 2}-.0996778{col 29}{space 2} .0061969{col 40}{space 1}  -16.09{col 49}{space 3}0.000{col 57}{space 4}-.1118234{col 70}{space 3}-.0875322
{txt}{space 9}22022  {c |}{col 17}{res}{space 2} .0130494{col 29}{space 2} .0030704{col 40}{space 1}    4.25{col 49}{space 3}0.000{col 57}{space 4} .0070315{col 70}{space 3} .0190673
{txt}{space 9}22044  {c |}{col 17}{res}{space 2}-.0439606{col 29}{space 2} .0041541{col 40}{space 1}  -10.58{col 49}{space 3}0.000{col 57}{space 4}-.0521026{col 70}{space 3}-.0358187
{txt}{space 9}22066  {c |}{col 17}{res}{space 2}-.0281203{col 29}{space 2} .0050896{col 40}{space 1}   -5.53{col 49}{space 3}0.000{col 57}{space 4}-.0380956{col 70}{space 3}-.0181449
{txt}{space 9}22088  {c |}{col 17}{res}{space 2}-.0191704{col 29}{space 2} .0063284{col 40}{space 1}   -3.03{col 49}{space 3}0.002{col 57}{space 4}-.0315739{col 70}{space 3}-.0067669
{txt}{space 9}22110  {c |}{col 17}{res}{space 2}-.0087737{col 29}{space 2} .0074359{col 40}{space 1}   -1.18{col 49}{space 3}0.238{col 57}{space 4}-.0233477{col 70}{space 3} .0058003
{txt}{space 9}22132  {c |}{col 17}{res}{space 2} .0159676{col 29}{space 2} .0088146{col 40}{space 1}    1.81{col 49}{space 3}0.070{col 57}{space 4}-.0013088{col 70}{space 3}  .033244
{txt}{space 9}22154  {c |}{col 17}{res}{space 2} .0274359{col 29}{space 2} .0098631{col 40}{space 1}    2.78{col 49}{space 3}0.005{col 57}{space 4} .0081045{col 70}{space 3} .0467672
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{txt}{space 9}48096  {c |}{col 17}{res}{space 2}-.0277902{col 29}{space 2} .0057148{col 40}{space 1}   -4.86{col 49}{space 3}0.000{col 57}{space 4} -.038991{col 70}{space 3}-.0165894
{txt}{space 9}48144  {c |}{col 17}{res}{space 2}-.0372102{col 29}{space 2}   .00693{col 40}{space 1}   -5.37{col 49}{space 3}0.000{col 57}{space 4}-.0507927{col 70}{space 3}-.0236277
{txt}{space 9}48192  {c |}{col 17}{res}{space 2}-.0612284{col 29}{space 2} .0080063{col 40}{space 1}   -7.65{col 49}{space 3}0.000{col 57}{space 4}-.0769204{col 70}{space 3}-.0455363
{txt}{space 9}48240  {c |}{col 17}{res}{space 2}-.0580885{col 29}{space 2} .0084011{col 40}{space 1}   -6.91{col 49}{space 3}0.000{col 57}{space 4}-.0745543{col 70}{space 3}-.0416226
{txt}{space 9}48288  {c |}{col 17}{res}{space 2}-.0212858{col 29}{space 2} .0071429{col 40}{space 1}   -2.98{col 49}{space 3}0.003{col 57}{space 4}-.0352857{col 70}{space 3} -.007286
{txt}{space 9}48336  {c |}{col 17}{res}{space 2}-.0075945{col 29}{space 2} .0104846{col 40}{space 1}   -0.72{col 49}{space 3}0.469{col 57}{space 4}-.0281439{col 70}{space 3} .0129549
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{txt}{space 9}52052  {c |}{col 17}{res}{space 2} .1146259{col 29}{space 2} .0126415{col 40}{space 1}    9.07{col 49}{space 3}0.000{col 57}{space 4}  .089849{col 70}{space 3} .1394028
{txt}{space 9}52104  {c |}{col 17}{res}{space 2} .0177039{col 29}{space 2} .0127892{col 40}{space 1}    1.38{col 49}{space 3}0.166{col 57}{space 4}-.0073625{col 70}{space 3} .0427704
{txt}{space 9}52156  {c |}{col 17}{res}{space 2}-.0047007{col 29}{space 2} .0104074{col 40}{space 1}   -0.45{col 49}{space 3}0.652{col 57}{space 4}-.0250989{col 70}{space 3} .0156974
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store urban2
{txt}
{com}. 
. 
. coefplot full2 nourban2 urban2 || full1 nourban1 urban1, keep(*.GL) vertical yline(0, lpattern(dash) lwidth(thick) lcolor(cranberry)) mlabel rescale(100) format(%9.2g) mlabposition(3) mlabgap(*2) ci(95 90) legend(row(1))
{res}{txt}
{com}. 
. 
. ///FIGURE 3///
> 
. 
. logit contplt i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-58074.493}  
Iteration 1:{space 3}log pseudolikelihood = {res:-55740.749}  
Iteration 2:{space 3}log pseudolikelihood = {res:-55657.145}  
Iteration 3:{space 3}log pseudolikelihood = {res:-55656.454}  
Iteration 4:{space 3}log pseudolikelihood = {res:-55656.454}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,673
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-55656.454{txt}{col 49}Pseudo R2{col 67}= {res}    0.0416

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}        contplt{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2}  .139097{col 29}{space 2}   .13631{col 40}{space 1}    1.02{col 49}{space 3}0.308{col 57}{space 4}-.1280657{col 70}{space 3} .4062597
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .3244815{col 29}{space 2} .0466491{col 40}{space 1}    6.96{col 49}{space 3}0.000{col 57}{space 4} .2330508{col 70}{space 3} .4159121
{txt}{space 11}agea {c |}{col 17}{res}{space 2}  .011805{col 29}{space 2} .0029698{col 40}{space 1}    3.97{col 49}{space 3}0.000{col 57}{space 4} .0059843{col 70}{space 3} .0176257
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0982128{col 29}{space 2} .0060985{col 40}{space 1}   16.10{col 49}{space 3}0.000{col 57}{space 4}   .08626{col 70}{space 3} .1101657
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0442931{col 29}{space 2} .0543719{col 40}{space 1}    0.81{col 49}{space 3}0.415{col 57}{space 4}-.0622739{col 70}{space 3} .1508601
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} -.065338{col 29}{space 2}  .047926{col 40}{space 1}   -1.36{col 49}{space 3}0.173{col 57}{space 4}-.1592712{col 70}{space 3} .0285952
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2}-.1388692{col 29}{space 2} .1094594{col 40}{space 1}   -1.27{col 49}{space 3}0.205{col 57}{space 4}-.3534056{col 70}{space 3} .0756672
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.1126239{col 29}{space 2} .0424966{col 40}{space 1}   -2.65{col 49}{space 3}0.008{col 57}{space 4}-.1959157{col 70}{space 3}-.0293321
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.2211538{col 29}{space 2} .0651396{col 40}{space 1}   -3.40{col 49}{space 3}0.001{col 57}{space 4}-.3488251{col 70}{space 3}-.0934826
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .2880465{col 29}{space 2} .0682768{col 40}{space 1}    4.22{col 49}{space 3}0.000{col 57}{space 4} .1542263{col 70}{space 3} .4218666
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.4208935{col 29}{space 2} .0129418{col 40}{space 1}  -32.52{col 49}{space 3}0.000{col 57}{space 4}-.4462591{col 70}{space 3} -.395528
{txt}{space 10}4012  {c |}{col 17}{res}{space 2} .0611683{col 29}{space 2} .0122702{col 40}{space 1}    4.99{col 49}{space 3}0.000{col 57}{space 4} .0371191{col 70}{space 3} .0852175
{txt}{space 10}4016  {c |}{col 17}{res}{space 2}-.2012739{col 29}{space 2} .0139944{col 40}{space 1}  -14.38{col 49}{space 3}0.000{col 57}{space 4}-.2287025{col 70}{space 3}-.1738454
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.5913914{col 29}{space 2} .0154035{col 40}{space 1}  -38.39{col 49}{space 3}0.000{col 57}{space 4}-.6215816{col 70}{space 3}-.5612011
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.2425221{col 29}{space 2}  .016629{col 40}{space 1}  -14.58{col 49}{space 3}0.000{col 57}{space 4}-.2751143{col 70}{space 3}  -.20993
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.3125165{col 29}{space 2} .0212999{col 40}{space 1}  -14.67{col 49}{space 3}0.000{col 57}{space 4}-.3542635{col 70}{space 3}-.2707694
{txt}{space 10}4032  {c |}{col 17}{res}{space 2}-.3414128{col 29}{space 2} .0200576{col 40}{space 1}  -17.02{col 49}{space 3}0.000{col 57}{space 4} -.380725{col 70}{space 3}-.3021007
{txt}{space 10}8008  {c |}{col 17}{res}{space 2} .2012976{col 29}{space 2}  .012906{col 40}{space 1}   15.60{col 49}{space 3}0.000{col 57}{space 4} .1760024{col 70}{space 3} .2265929
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{txt}{space 10}8024  {c |}{col 17}{res}{space 2}-.5272455{col 29}{space 2} .0207564{col 40}{space 1}  -25.40{col 49}{space 3}0.000{col 57}{space 4}-.5679273{col 70}{space 3}-.4865638
{txt}{space 10}8032  {c |}{col 17}{res}{space 2}-.4157275{col 29}{space 2} .0083622{col 40}{space 1}  -49.71{col 49}{space 3}0.000{col 57}{space 4}-.4321173{col 70}{space 3}-.3993378
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{txt}{space 9}14042  {c |}{col 17}{res}{space 2}-.4967693{col 29}{space 2} .0381719{col 40}{space 1}  -13.01{col 49}{space 3}0.000{col 57}{space 4}-.5715848{col 70}{space 3}-.4219539
{txt}{space 9}14056  {c |}{col 17}{res}{space 2}-.1731261{col 29}{space 2} .0304749{col 40}{space 1}   -5.68{col 49}{space 3}0.000{col 57}{space 4}-.2328558{col 70}{space 3}-.1133964
{txt}{space 9}14070  {c |}{col 17}{res}{space 2}-.2355459{col 29}{space 2} .0280076{col 40}{space 1}   -8.41{col 49}{space 3}0.000{col 57}{space 4}-.2904397{col 70}{space 3}-.1806521
{txt}{space 9}14084  {c |}{col 17}{res}{space 2}-.2569017{col 29}{space 2} .0359366{col 40}{space 1}   -7.15{col 49}{space 3}0.000{col 57}{space 4}-.3273362{col 70}{space 3}-.1864672
{txt}{space 9}14098  {c |}{col 17}{res}{space 2}-.2191161{col 29}{space 2} .0335841{col 40}{space 1}   -6.52{col 49}{space 3}0.000{col 57}{space 4}-.2849397{col 70}{space 3}-.1532925
{txt}{space 9}14112  {c |}{col 17}{res}{space 2}-.2123724{col 29}{space 2} .0284999{col 40}{space 1}   -7.45{col 49}{space 3}0.000{col 57}{space 4}-.2682311{col 70}{space 3}-.1565137
{txt}{space 9}20020  {c |}{col 17}{res}{space 2}-.2837265{col 29}{space 2} .0229978{col 40}{space 1}  -12.34{col 49}{space 3}0.000{col 57}{space 4}-.3288013{col 70}{space 3}-.2386517
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-3.632147{col 29}{space 2} .2776014{col 40}{space 1}  -13.08{col 49}{space 3}0.000{col 57}{space 4}-4.176236{col 70}{space 3}-3.088059
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store a1
{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,673
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(contplt), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0198133{col 29}{space 2} .0201218{col 40}{space 1}    0.98{col 49}{space 3}0.325{col 57}{space 4}-.0196247{col 70}{space 3} .0592512
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0443297{col 29}{space 2} .0063674{col 40}{space 1}    6.96{col 49}{space 3}0.000{col 57}{space 4} .0318497{col 70}{space 3} .0568096
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{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0134337{col 29}{space 2} .0008059{col 40}{space 1}   16.67{col 49}{space 3}0.000{col 57}{space 4} .0118542{col 70}{space 3} .0150132
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0060585{col 29}{space 2} .0074194{col 40}{space 1}    0.82{col 49}{space 3}0.414{col 57}{space 4}-.0084832{col 70}{space 3} .0206001
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} -.009142{col 29}{space 2} .0065591{col 40}{space 1}   -1.39{col 49}{space 3}0.163{col 57}{space 4}-.0219976{col 70}{space 3} .0037137
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2}-.0190038{col 29}{space 2} .0144998{col 40}{space 1}   -1.31{col 49}{space 3}0.190{col 57}{space 4}-.0474229{col 70}{space 3} .0094152
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0155354{col 29}{space 2} .0057156{col 40}{space 1}   -2.72{col 49}{space 3}0.007{col 57}{space 4}-.0267377{col 70}{space 3} -.004333
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.0295114{col 29}{space 2} .0083104{col 40}{space 1}   -3.55{col 49}{space 3}0.000{col 57}{space 4}-.0457995{col 70}{space 3}-.0132232
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .0401673{col 29}{space 2} .0095686{col 40}{space 1}    4.20{col 49}{space 3}0.000{col 57}{space 4} .0214132{col 70}{space 3} .0589213
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.0584558{col 29}{space 2} .0025972{col 40}{space 1}  -22.51{col 49}{space 3}0.000{col 57}{space 4}-.0635461{col 70}{space 3}-.0533654
{txt}{space 10}4012  {c |}{col 17}{res}{space 2} .0097578{col 29}{space 2} .0018544{col 40}{space 1}    5.26{col 49}{space 3}0.000{col 57}{space 4} .0061232{col 70}{space 3} .0133925
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{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.0779759{col 29}{space 2} .0029137{col 40}{space 1}  -26.76{col 49}{space 3}0.000{col 57}{space 4}-.0836866{col 70}{space 3}-.0722651
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.0355141{col 29}{space 2} .0027464{col 40}{space 1}  -12.93{col 49}{space 3}0.000{col 57}{space 4}-.0408969{col 70}{space 3}-.0301313
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.0448318{col 29}{space 2} .0034806{col 40}{space 1}  -12.88{col 49}{space 3}0.000{col 57}{space 4}-.0516537{col 70}{space 3}-.0380099
{txt}{space 10}4032  {c |}{col 17}{res}{space 2} -.048559{col 29}{space 2} .0031519{col 40}{space 1}  -15.41{col 49}{space 3}0.000{col 57}{space 4}-.0547365{col 70}{space 3}-.0423814
{txt}{space 10}8008  {c |}{col 17}{res}{space 2} .0333248{col 29}{space 2} .0027823{col 40}{space 1}   11.98{col 49}{space 3}0.000{col 57}{space 4} .0278716{col 70}{space 3}  .038778
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b1
{txt}
{com}. 
. logit wrkprty i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-22765.589}  
Iteration 1:{space 3}log pseudolikelihood = {res:-21764.905}  
Iteration 2:{space 3}log pseudolikelihood = {res:-21541.761}  
Iteration 3:{space 3}log pseudolikelihood = {res:-21541.343}  
Iteration 4:{space 3}log pseudolikelihood = {res:-21541.343}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,676
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-21541.343{txt}{col 49}Pseudo R2{col 67}= {res}    0.0538

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}        wrkprty{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .2258529{col 29}{space 2} .1080251{col 40}{space 1}    2.09{col 49}{space 3}0.037{col 57}{space 4} .0141275{col 70}{space 3} .4375783
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .5500718{col 29}{space 2}  .078651{col 40}{space 1}    6.99{col 49}{space 3}0.000{col 57}{space 4} .3959186{col 70}{space 3}  .704225
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0189359{col 29}{space 2}   .00354{col 40}{space 1}    5.35{col 49}{space 3}0.000{col 57}{space 4} .0119977{col 70}{space 3} .0258741
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0895663{col 29}{space 2} .0061316{col 40}{space 1}   14.61{col 49}{space 3}0.000{col 57}{space 4} .0775485{col 70}{space 3} .1015841
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .1007318{col 29}{space 2} .0326483{col 40}{space 1}    3.09{col 49}{space 3}0.002{col 57}{space 4} .0367423{col 70}{space 3} .1647212
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0513084{col 29}{space 2}  .182903{col 40}{space 1}    0.28{col 49}{space 3}0.779{col 57}{space 4}-.3071749{col 70}{space 3} .4097917
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store a2
{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,676
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(wrkprty), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0101643{col 29}{space 2} .0053212{col 40}{space 1}    1.91{col 49}{space 3}0.056{col 57}{space 4}-.0002651{col 70}{space 3} .0205937
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0218743{col 29}{space 2} .0029905{col 40}{space 1}    7.31{col 49}{space 3}0.000{col 57}{space 4}  .016013{col 70}{space 3} .0277357
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{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.0077181{col 29}{space 2} .0038249{col 40}{space 1}   -2.02{col 49}{space 3}0.044{col 57}{space 4}-.0152148{col 70}{space 3}-.0002215
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .0044556{col 29}{space 2} .0040241{col 40}{space 1}    1.11{col 49}{space 3}0.268{col 57}{space 4}-.0034315{col 70}{space 3} .0123428
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 9}56448  {c |}{col 17}{res}{space 2}-.0097013{col 29}{space 2} .0012906{col 40}{space 1}   -7.52{col 49}{space 3}0.000{col 57}{space 4}-.0122309{col 70}{space 3}-.0071717
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b2
{txt}
{com}. 
. logit wrkorg i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -62877.61}  
Iteration 1:{space 3}log pseudolikelihood = {res:-57415.067}  
Iteration 2:{space 3}log pseudolikelihood = {res:-57035.602}  
Iteration 3:{space 3}log pseudolikelihood = {res:-57028.846}  
Iteration 4:{space 3}log pseudolikelihood = {res:-57028.791}  
Iteration 5:{space 3}log pseudolikelihood = {res:-57028.791}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,634
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(9)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-57028.791{txt}{col 49}Pseudo R2{col 67}= {res}    0.0930

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}         wrkorg{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2}-.0139361{col 29}{space 2} .0749309{col 40}{space 1}   -0.19{col 49}{space 3}0.852{col 57}{space 4} -.160798{col 70}{space 3} .1329258
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2}  .311832{col 29}{space 2} .0323094{col 40}{space 1}    9.65{col 49}{space 3}0.000{col 57}{space 4} .2485067{col 70}{space 3} .3751573
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0122188{col 29}{space 2} .0022099{col 40}{space 1}    5.53{col 49}{space 3}0.000{col 57}{space 4} .0078876{col 70}{space 3}   .01655
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{txt}{space 12}swi {c |}{col 17}{res}{space 2} .1862337{col 29}{space 2} .0356312{col 40}{space 1}    5.23{col 49}{space 3}0.000{col 57}{space 4} .1163978{col 70}{space 3} .2560697
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.1487109{col 29}{space 2}  .081374{col 40}{space 1}   -1.83{col 49}{space 3}0.068{col 57}{space 4}-.3082011{col 70}{space 3} .0107793
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .3183961{col 29}{space 2} .1329931{col 40}{space 1}    2.39{col 49}{space 3}0.017{col 57}{space 4} .0577344{col 70}{space 3} .5790577
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0836756{col 29}{space 2} .0500942{col 40}{space 1}   -1.67{col 49}{space 3}0.095{col 57}{space 4}-.1818584{col 70}{space 3} .0145072
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.1085432{col 29}{space 2} .0472287{col 40}{space 1}   -2.30{col 49}{space 3}0.022{col 57}{space 4}-.2011097{col 70}{space 3}-.0159767
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .2594162{col 29}{space 2} .0990844{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4} .0652144{col 70}{space 3} .4536181
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-3.938592{col 29}{space 2} .2190251{col 40}{space 1}  -17.98{col 49}{space 3}0.000{col 57}{space 4}-4.367873{col 70}{space 3}-3.509311
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store a3
{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,634
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(wrkorg), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2}-.0019975{col 29}{space 2} .0107016{col 40}{space 1}   -0.19{col 49}{space 3}0.852{col 57}{space 4}-.0229721{col 70}{space 3} .0189772
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0210051{col 29}{space 2} .0109411{col 40}{space 1}   -1.92{col 49}{space 3}0.055{col 57}{space 4}-.0424492{col 70}{space 3}  .000439
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{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}  .037794{col 29}{space 2} .0145459{col 40}{space 1}    2.60{col 49}{space 3}0.009{col 57}{space 4} .0092845{col 70}{space 3} .0663036
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .1077108{col 29}{space 2} .0072569{col 40}{space 1}   14.84{col 49}{space 3}0.000{col 57}{space 4} .0934876{col 70}{space 3} .1219339
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b3
{txt}
{com}. 
. logit badge i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-34375.032}  
Iteration 1:{space 3}log pseudolikelihood = {res:-33132.267}  
Iteration 2:{space 3}log pseudolikelihood = {res:-32543.924}  
Iteration 3:{space 3}log pseudolikelihood = {res:-32527.595}  
Iteration 4:{space 3}log pseudolikelihood = {res:-32527.302}  
Iteration 5:{space 3}log pseudolikelihood = {res:-32527.302}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,633
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(9)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-32527.302{txt}{col 49}Pseudo R2{col 67}= {res}    0.0538

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}          badge{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2}  .354976{col 29}{space 2} .1233733{col 40}{space 1}    2.88{col 49}{space 3}0.004{col 57}{space 4} .1131687{col 70}{space 3} .5967832
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2}-.0800018{col 29}{space 2} .0744487{col 40}{space 1}   -1.07{col 49}{space 3}0.283{col 57}{space 4}-.2259186{col 70}{space 3} .0659149
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0056324{col 29}{space 2} .0016069{col 40}{space 1}    3.51{col 49}{space 3}0.000{col 57}{space 4}  .002483{col 70}{space 3} .0087818
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0746258{col 29}{space 2} .0050333{col 40}{space 1}   14.83{col 49}{space 3}0.000{col 57}{space 4} .0647608{col 70}{space 3} .0844909
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0484373{col 29}{space 2} .0227661{col 40}{space 1}    2.13{col 49}{space 3}0.033{col 57}{space 4} .0038166{col 70}{space 3}  .093058
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .1399537{col 29}{space 2} .0617765{col 40}{space 1}    2.27{col 49}{space 3}0.023{col 57}{space 4}  .018874{col 70}{space 3} .2610335
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .2685864{col 29}{space 2} .1242047{col 40}{space 1}    2.16{col 49}{space 3}0.031{col 57}{space 4} .0251497{col 70}{space 3} .5120232
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.2450662{col 29}{space 2} .0433151{col 40}{space 1}   -5.66{col 49}{space 3}0.000{col 57}{space 4}-.3299623{col 70}{space 3}-.1601701
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} -.203343{col 29}{space 2} .0746099{col 40}{space 1}   -2.73{col 49}{space 3}0.006{col 57}{space 4}-.3495757{col 70}{space 3}-.0571102
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.0676124{col 29}{space 2} .0383061{col 40}{space 1}   -1.77{col 49}{space 3}0.078{col 57}{space 4}-.1426909{col 70}{space 3} .0074661
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.4080054{col 29}{space 2} .0054218{col 40}{space 1}  -75.25{col 49}{space 3}0.000{col 57}{space 4}-.4186321{col 70}{space 3}-.3973788
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-3.836263{col 29}{space 2} .1858109{col 40}{space 1}  -20.65{col 49}{space 3}0.000{col 57}{space 4}-4.200445{col 70}{space 3} -3.47208
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store a4
{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,633
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(badge), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0279205{col 29}{space 2} .0109981{col 40}{space 1}    2.54{col 49}{space 3}0.011{col 57}{space 4} .0063647{col 70}{space 3} .0494763
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2}-.0054957{col 29}{space 2} .0051223{col 40}{space 1}   -1.07{col 49}{space 3}0.283{col 57}{space 4}-.0155352{col 70}{space 3} .0045438
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{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0033258{col 29}{space 2}   .00156{col 40}{space 1}    2.13{col 49}{space 3}0.033{col 57}{space 4} .0002683{col 70}{space 3} .0063834
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2} .0107263{col 29}{space 2} .0048596{col 40}{space 1}    2.21{col 49}{space 3}0.027{col 57}{space 4} .0012016{col 70}{space 3} .0202509
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{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0161477{col 29}{space 2} .0028083{col 40}{space 1}   -5.75{col 49}{space 3}0.000{col 57}{space 4}-.0216519{col 70}{space 3}-.0106436
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.0136195{col 29}{space 2}  .004806{col 40}{space 1}   -2.83{col 49}{space 3}0.005{col 57}{space 4}-.0230392{col 70}{space 3}-.0041999
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.0046124{col 29}{space 2}  .002591{col 40}{space 1}   -1.78{col 49}{space 3}0.075{col 57}{space 4}-.0096906{col 70}{space 3} .0004658
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 9}14070  {c |}{col 17}{res}{space 2}-.0255231{col 29}{space 2} .0010646{col 40}{space 1}  -23.97{col 49}{space 3}0.000{col 57}{space 4}-.0276097{col 70}{space 3}-.0234366
{txt}{space 9}14084  {c |}{col 17}{res}{space 2}-.0255454{col 29}{space 2} .0014018{col 40}{space 1}  -18.22{col 49}{space 3}0.000{col 57}{space 4}-.0282928{col 70}{space 3} -.022798
{txt}{space 9}14098  {c |}{col 17}{res}{space 2}-.0216335{col 29}{space 2} .0015449{col 40}{space 1}  -14.00{col 49}{space 3}0.000{col 57}{space 4}-.0246615{col 70}{space 3}-.0186055
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b4
{txt}
{com}. 
. logit sgnptit i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-79761.344}  
Iteration 1:{space 3}log pseudolikelihood = {res:-75151.321}  
Iteration 2:{space 3}log pseudolikelihood = {res:-75001.722}  
Iteration 3:{space 3}log pseudolikelihood = {res:-74997.569}  
Iteration 4:{space 3}log pseudolikelihood = {res:-74997.552}  
Iteration 5:{space 3}log pseudolikelihood = {res:-74997.552}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,396
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(9)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-74997.552{txt}{col 49}Pseudo R2{col 67}= {res}    0.0597

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}        sgnptit{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .1596635{col 29}{space 2} .0537193{col 40}{space 1}    2.97{col 49}{space 3}0.003{col 57}{space 4} .0543757{col 70}{space 3} .2649513
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} -.167154{col 29}{space 2} .0429832{col 40}{space 1}   -3.89{col 49}{space 3}0.000{col 57}{space 4}-.2513995{col 70}{space 3}-.0829086
{txt}{space 11}agea {c |}{col 17}{res}{space 2}-.0002557{col 29}{space 2} .0016688{col 40}{space 1}   -0.15{col 49}{space 3}0.878{col 57}{space 4}-.0035264{col 70}{space 3}  .003015
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .1015775{col 29}{space 2} .0070801{col 40}{space 1}   14.35{col 49}{space 3}0.000{col 57}{space 4} .0877007{col 70}{space 3} .1154543
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0700724{col 29}{space 2} .0235798{col 40}{space 1}    2.97{col 49}{space 3}0.003{col 57}{space 4} .0238568{col 70}{space 3}  .116288
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0734218{col 29}{space 2} .0784472{col 40}{space 1}   -0.94{col 49}{space 3}0.349{col 57}{space 4}-.2271755{col 70}{space 3} .0803318
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .1106283{col 29}{space 2} .0972887{col 40}{space 1}    1.14{col 49}{space 3}0.255{col 57}{space 4}-.0800541{col 70}{space 3} .3013107
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.1426659{col 29}{space 2} .0411444{col 40}{space 1}   -3.47{col 49}{space 3}0.001{col 57}{space 4}-.2233074{col 70}{space 3}-.0620243
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} -.204785{col 29}{space 2} .0134934{col 40}{space 1}  -15.18{col 49}{space 3}0.000{col 57}{space 4}-.2312316{col 70}{space 3}-.1783385
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.0665019{col 29}{space 2}  .051728{col 40}{space 1}   -1.29{col 49}{space 3}0.199{col 57}{space 4}-.1678869{col 70}{space 3}  .034883
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2} -.619671{col 29}{space 2} .0030051{col 40}{space 1} -206.21{col 49}{space 3}0.000{col 57}{space 4}-.6255608{col 70}{space 3}-.6137812
{txt}{space 10}4012  {c |}{col 17}{res}{space 2}-.1215088{col 29}{space 2} .0087822{col 40}{space 1}  -13.84{col 49}{space 3}0.000{col 57}{space 4}-.1387217{col 70}{space 3} -.104296
{txt}{space 10}4016  {c |}{col 17}{res}{space 2}-.3614957{col 29}{space 2}  .007299{col 40}{space 1}  -49.53{col 49}{space 3}0.000{col 57}{space 4}-.3758015{col 70}{space 3}-.3471899
{txt}{space 10}4020  {c |}{col 17}{res}{space 2} -.783488{col 29}{space 2} .0074689{col 40}{space 1} -104.90{col 49}{space 3}0.000{col 57}{space 4}-.7981267{col 70}{space 3}-.7688493
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.7557014{col 29}{space 2} .0102413{col 40}{space 1}  -73.79{col 49}{space 3}0.000{col 57}{space 4} -.775774{col 70}{space 3}-.7356289
{txt}{space 10}4028  {c |}{col 17}{res}{space 2}-.6736451{col 29}{space 2} .0088251{col 40}{space 1}  -76.33{col 49}{space 3}0.000{col 57}{space 4}-.6909419{col 70}{space 3}-.6563483
{txt}{space 10}4032  {c |}{col 17}{res}{space 2} -.552409{col 29}{space 2}  .014365{col 40}{space 1}  -38.46{col 49}{space 3}0.000{col 57}{space 4}-.5805638{col 70}{space 3}-.5242542
{txt}{space 10}8008  {c |}{col 17}{res}{space 2} .4244484{col 29}{space 2}  .009308{col 40}{space 1}   45.60{col 49}{space 3}0.000{col 57}{space 4}  .406205{col 70}{space 3} .4426917
{txt}{space 10}8016  {c |}{col 17}{res}{space 2} .4692314{col 29}{space 2} .0142139{col 40}{space 1}   33.01{col 49}{space 3}0.000{col 57}{space 4} .4413727{col 70}{space 3} .4970902
{txt}{space 10}8024  {c |}{col 17}{res}{space 2} .0438232{col 29}{space 2} .0148263{col 40}{space 1}    2.96{col 49}{space 3}0.003{col 57}{space 4} .0147641{col 70}{space 3} .0728823
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-1.968854{col 29}{space 2} .2120675{col 40}{space 1}   -9.28{col 49}{space 3}0.000{col 57}{space 4}-2.384499{col 70}{space 3} -1.55321
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,396
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(sgnptit), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0333388{col 29}{space 2} .0113277{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4}  .011137{col 70}{space 3} .0555406
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2}-.0341589{col 29}{space 2} .0088341{col 40}{space 1}   -3.87{col 49}{space 3}0.000{col 57}{space 4}-.0514734{col 70}{space 3}-.0168445
{txt}{space 11}agea {c |}{col 17}{res}{space 2}-.0000522{col 29}{space 2}  .000341{col 40}{space 1}   -0.15{col 49}{space 3}0.878{col 57}{space 4}-.0007205{col 70}{space 3}  .000616
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0207551{col 29}{space 2} .0013429{col 40}{space 1}   15.46{col 49}{space 3}0.000{col 57}{space 4}  .018123{col 70}{space 3} .0233873
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0143178{col 29}{space 2} .0047436{col 40}{space 1}    3.02{col 49}{space 3}0.003{col 57}{space 4} .0050205{col 70}{space 3}  .023615
{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b5
{txt}
{com}. 
. logit pbldmn i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -38951.21}  
Iteration 1:{space 3}log pseudolikelihood = {res:-36129.406}  
Iteration 2:{space 3}log pseudolikelihood = {res:-35148.258}  
Iteration 3:{space 3}log pseudolikelihood = {res: -35133.46}  
Iteration 4:{space 3}log pseudolikelihood = {res:-35133.348}  
Iteration 5:{space 3}log pseudolikelihood = {res:-35133.348}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,663
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-35133.348{txt}{col 49}Pseudo R2{col 67}= {res}    0.0980

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}         pbldmn{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .5602121{col 29}{space 2} .0711374{col 40}{space 1}    7.88{col 49}{space 3}0.000{col 57}{space 4} .4207853{col 70}{space 3} .6996388
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .1359249{col 29}{space 2} .0662352{col 40}{space 1}    2.05{col 49}{space 3}0.040{col 57}{space 4} .0061063{col 70}{space 3} .2657436
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{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2}  .079414{col 29}{space 2}  .006228{col 40}{space 1}   12.75{col 49}{space 3}0.000{col 57}{space 4} .0672073{col 70}{space 3} .0916207
{txt}{space 12}swi {c |}{col 17}{res}{space 2} -.009077{col 29}{space 2}  .017723{col 40}{space 1}   -0.51{col 49}{space 3}0.609{col 57}{space 4}-.0438134{col 70}{space 3} .0256594
{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .4093631{col 29}{space 2} .1205275{col 40}{space 1}    3.40{col 49}{space 3}0.001{col 57}{space 4} .1731336{col 70}{space 3} .6455927
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{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.3191922{col 29}{space 2} .0618018{col 40}{space 1}   -5.16{col 49}{space 3}0.000{col 57}{space 4}-.4403216{col 70}{space 3}-.1980628
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-3.492891{col 29}{space 2}  .171252{col 40}{space 1}  -20.40{col 49}{space 3}0.000{col 57}{space 4}-3.828539{col 70}{space 3}-3.157243
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,663
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(pbldmn), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0526404{col 29}{space 2} .0077685{col 40}{space 1}    6.78{col 49}{space 3}0.000{col 57}{space 4} .0374144{col 70}{space 3} .0678665
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2} .0105504{col 29}{space 2} .0050939{col 40}{space 1}    2.07{col 49}{space 3}0.038{col 57}{space 4} .0005666{col 70}{space 3} .0205343
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{txt}{space 12}swi {c |}{col 17}{res}{space 2}-.0007055{col 29}{space 2} .0013769{col 40}{space 1}   -0.51{col 49}{space 3}0.608{col 57}{space 4}-.0034041{col 70}{space 3} .0019931
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0127356{col 29}{space 2} .0092657{col 40}{space 1}   -1.37{col 49}{space 3}0.169{col 57}{space 4}-.0308961{col 70}{space 3} .0054249
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{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0253873{col 29}{space 2} .0043722{col 40}{space 1}   -5.81{col 49}{space 3}0.000{col 57}{space 4}-.0339567{col 70}{space 3} -.016818
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.0307433{col 29}{space 2} .0036117{col 40}{space 1}   -8.51{col 49}{space 3}0.000{col 57}{space 4} -.037822{col 70}{space 3}-.0236646
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2}-.0241552{col 29}{space 2} .0044992{col 40}{space 1}   -5.37{col 49}{space 3}0.000{col 57}{space 4}-.0329736{col 70}{space 3}-.0153369
{txt}{space 15} {c |}
{space 7}election {c |}
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{txt}{space 9}14084  {c |}{col 17}{res}{space 2}-.0125553{col 29}{space 2} .0008895{col 40}{space 1}  -14.12{col 49}{space 3}0.000{col 57}{space 4}-.0142987{col 70}{space 3}-.0108119
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{txt}{space 9}20060  {c |}{col 17}{res}{space 2} .1096546{col 29}{space 2} .0007141{col 40}{space 1}  153.57{col 49}{space 3}0.000{col 57}{space 4} .1082551{col 70}{space 3} .1110542
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{txt}{space 9}48048  {c |}{col 17}{res}{space 2}  .001797{col 29}{space 2} .0008975{col 40}{space 1}    2.00{col 49}{space 3}0.045{col 57}{space 4}  .000038{col 70}{space 3} .0035561
{txt}{space 9}48096  {c |}{col 17}{res}{space 2}  .018333{col 29}{space 2} .0008061{col 40}{space 1}   22.74{col 49}{space 3}0.000{col 57}{space 4} .0167531{col 70}{space 3}  .019913
{txt}{space 9}48144  {c |}{col 17}{res}{space 2}-.0061428{col 29}{space 2} .0008503{col 40}{space 1}   -7.22{col 49}{space 3}0.000{col 57}{space 4}-.0078093{col 70}{space 3}-.0044762
{txt}{space 9}48192  {c |}{col 17}{res}{space 2}-.0141758{col 29}{space 2} .0008529{col 40}{space 1}  -16.62{col 49}{space 3}0.000{col 57}{space 4}-.0158475{col 70}{space 3}-.0125042
{txt}{space 9}48240  {c |}{col 17}{res}{space 2} .0044866{col 29}{space 2} .0008457{col 40}{space 1}    5.31{col 49}{space 3}0.000{col 57}{space 4} .0028291{col 70}{space 3} .0061442
{txt}{space 9}48288  {c |}{col 17}{res}{space 2} .0081473{col 29}{space 2} .0010175{col 40}{space 1}    8.01{col 49}{space 3}0.000{col 57}{space 4} .0061531{col 70}{space 3} .0101416
{txt}{space 9}48336  {c |}{col 17}{res}{space 2} .0064536{col 29}{space 2} .0012331{col 40}{space 1}    5.23{col 49}{space 3}0.000{col 57}{space 4} .0040368{col 70}{space 3} .0088703
{txt}{space 9}48384  {c |}{col 17}{res}{space 2} .0077688{col 29}{space 2}  .001329{col 40}{space 1}    5.85{col 49}{space 3}0.000{col 57}{space 4}  .005164{col 70}{space 3} .0103736
{txt}{space 9}52052  {c |}{col 17}{res}{space 2}-.0179893{col 29}{space 2} .0018738{col 40}{space 1}   -9.60{col 49}{space 3}0.000{col 57}{space 4}-.0216619{col 70}{space 3}-.0143166
{txt}{space 9}52104  {c |}{col 17}{res}{space 2} -.046678{col 29}{space 2} .0010841{col 40}{space 1}  -43.06{col 49}{space 3}0.000{col 57}{space 4}-.0488029{col 70}{space 3}-.0445531
{txt}{space 9}52156  {c |}{col 17}{res}{space 2}-.0339113{col 29}{space 2} .0013553{col 40}{space 1}  -25.02{col 49}{space 3}0.000{col 57}{space 4}-.0365676{col 70}{space 3}-.0312551
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{txt}{space 9}52312  {c |}{col 17}{res}{space 2} .0150929{col 29}{space 2} .0030911{col 40}{space 1}    4.88{col 49}{space 3}0.000{col 57}{space 4} .0090343{col 70}{space 3} .0211514
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{txt}{space 9}56056  {c |}{col 17}{res}{space 2}-.0262434{col 29}{space 2} .0007304{col 40}{space 1}  -35.93{col 49}{space 3}0.000{col 57}{space 4}-.0276749{col 70}{space 3}-.0248119
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{txt}{space 9}56280  {c |}{col 17}{res}{space 2}-.0470651{col 29}{space 2} .0004534{col 40}{space 1} -103.80{col 49}{space 3}0.000{col 57}{space 4}-.0479537{col 70}{space 3}-.0461764
{txt}{space 9}56336  {c |}{col 17}{res}{space 2}-.0090845{col 29}{space 2} .0006579{col 40}{space 1}  -13.81{col 49}{space 3}0.000{col 57}{space 4} -.010374{col 70}{space 3} -.007795
{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .0149151{col 29}{space 2} .0007867{col 40}{space 1}   18.96{col 49}{space 3}0.000{col 57}{space 4} .0133732{col 70}{space 3} .0164571
{txt}{space 9}56448  {c |}{col 17}{res}{space 2}   .01665{col 29}{space 2}  .000783{col 40}{space 1}   21.27{col 49}{space 3}0.000{col 57}{space 4} .0151154{col 70}{space 3} .0181846
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b6
{txt}
{com}. 
. logit bctprd i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-71405.251}  
Iteration 1:{space 3}log pseudolikelihood = {res:-65667.474}  
Iteration 2:{space 3}log pseudolikelihood = {res:-65292.317}  
Iteration 3:{space 3}log pseudolikelihood = {res:-65279.353}  
Iteration 4:{space 3}log pseudolikelihood = {res:-65279.188}  
Iteration 5:{space 3}log pseudolikelihood = {res:-65279.188}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}   110,485
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-65279.188{txt}{col 49}Pseudo R2{col 67}= {res}    0.0858

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}         bctprd{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .2025206{col 29}{space 2} .0147601{col 40}{space 1}   13.72{col 49}{space 3}0.000{col 57}{space 4} .1735914{col 70}{space 3} .2314499
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2}-.1958296{col 29}{space 2} .0140514{col 40}{space 1}  -13.94{col 49}{space 3}0.000{col 57}{space 4}-.2233698{col 70}{space 3}-.1682894
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0101646{col 29}{space 2} .0038225{col 40}{space 1}    2.66{col 49}{space 3}0.008{col 57}{space 4} .0026726{col 70}{space 3} .0176566
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .1098406{col 29}{space 2} .0059153{col 40}{space 1}   18.57{col 49}{space 3}0.000{col 57}{space 4} .0982469{col 70}{space 3} .1214343
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .0851891{col 29}{space 2} .0449285{col 40}{space 1}    1.90{col 49}{space 3}0.058{col 57}{space 4}-.0028692{col 70}{space 3} .1732474
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0538297{col 29}{space 2} .0602146{col 40}{space 1}   -0.89{col 49}{space 3}0.371{col 57}{space 4}-.1718482{col 70}{space 3} .0641888
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .2737145{col 29}{space 2} .0735614{col 40}{space 1}    3.72{col 49}{space 3}0.000{col 57}{space 4} .1295368{col 70}{space 3} .4178923
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.0375505{col 29}{space 2} .0516308{col 40}{space 1}   -0.73{col 49}{space 3}0.467{col 57}{space 4} -.138745{col 70}{space 3}  .063644
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2} -.242335{col 29}{space 2} .0826911{col 40}{space 1}   -2.93{col 49}{space 3}0.003{col 57}{space 4}-.4044066{col 70}{space 3}-.0802633
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .0075492{col 29}{space 2} .0546564{col 40}{space 1}    0.14{col 49}{space 3}0.890{col 57}{space 4}-.0995754{col 70}{space 3} .1146738
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2} -.320098{col 29}{space 2} .0102518{col 40}{space 1}  -31.22{col 49}{space 3}0.000{col 57}{space 4}-.3401911{col 70}{space 3}-.3000049
{txt}{space 10}4012  {c |}{col 17}{res}{space 2}-.0758379{col 29}{space 2} .0151709{col 40}{space 1}   -5.00{col 49}{space 3}0.000{col 57}{space 4}-.1055724{col 70}{space 3}-.0461035
{txt}{space 10}4016  {c |}{col 17}{res}{space 2}-.1886727{col 29}{space 2} .0191611{col 40}{space 1}   -9.85{col 49}{space 3}0.000{col 57}{space 4}-.2262278{col 70}{space 3}-.1511177
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.3694472{col 29}{space 2} .0167162{col 40}{space 1}  -22.10{col 49}{space 3}0.000{col 57}{space 4}-.4022103{col 70}{space 3} -.336684
{txt}{space 10}4024  {c |}{col 17}{res}{space 2}-.1620681{col 29}{space 2} .0210051{col 40}{space 1}   -7.72{col 49}{space 3}0.000{col 57}{space 4}-.2032372{col 70}{space 3}-.1208989
{txt}{space 10}4028  {c |}{col 17}{res}{space 2} .2053118{col 29}{space 2} .0228176{col 40}{space 1}    9.00{col 49}{space 3}0.000{col 57}{space 4} .1605901{col 70}{space 3} .2500334
{txt}{space 10}4032  {c |}{col 17}{res}{space 2} .0518616{col 29}{space 2} .0200274{col 40}{space 1}    2.59{col 49}{space 3}0.010{col 57}{space 4} .0126087{col 70}{space 3} .0911145
{txt}{space 10}8008  {c |}{col 17}{res}{space 2} 1.378749{col 29}{space 2} .0095153{col 40}{space 1}  144.90{col 49}{space 3}0.000{col 57}{space 4} 1.360099{col 70}{space 3} 1.397399
{txt}{space 10}8016  {c |}{col 17}{res}{space 2} 1.048542{col 29}{space 2} .0095235{col 40}{space 1}  110.10{col 49}{space 3}0.000{col 57}{space 4} 1.029876{col 70}{space 3} 1.067208
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{txt}{space 10}8048  {c |}{col 17}{res}{space 2} 1.062612{col 29}{space 2} .0169205{col 40}{space 1}   62.80{col 49}{space 3}0.000{col 57}{space 4} 1.029448{col 70}{space 3} 1.095775
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{txt}{space 9}14042  {c |}{col 17}{res}{space 2} .7909404{col 29}{space 2} .0254301{col 40}{space 1}   31.10{col 49}{space 3}0.000{col 57}{space 4} .7410983{col 70}{space 3} .8407824
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{txt}{space 9}14070  {c |}{col 17}{res}{space 2} 1.129921{col 29}{space 2} .0271745{col 40}{space 1}   41.58{col 49}{space 3}0.000{col 57}{space 4}  1.07666{col 70}{space 3} 1.183182
{txt}{space 9}14084  {c |}{col 17}{res}{space 2} 1.274207{col 29}{space 2} .0268276{col 40}{space 1}   47.50{col 49}{space 3}0.000{col 57}{space 4} 1.221625{col 70}{space 3} 1.326788
{txt}{space 9}14098  {c |}{col 17}{res}{space 2} 1.242794{col 29}{space 2}  .028372{col 40}{space 1}   43.80{col 49}{space 3}0.000{col 57}{space 4} 1.187186{col 70}{space 3} 1.298402
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{txt}{space 9}20020  {c |}{col 17}{res}{space 2}-.4223149{col 29}{space 2} .0092584{col 40}{space 1}  -45.61{col 49}{space 3}0.000{col 57}{space 4} -.440461{col 70}{space 3}-.4041688
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{txt}{space 9}24096  {c |}{col 17}{res}{space 2} 1.045727{col 29}{space 2}  .019098{col 40}{space 1}   54.76{col 49}{space 3}0.000{col 57}{space 4} 1.008295{col 70}{space 3} 1.083158
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-3.965216{col 29}{space 2} .2322204{col 40}{space 1}  -17.08{col 49}{space 3}0.000{col 57}{space 4}-4.420359{col 70}{space 3}-3.510072
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store a7
{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}   110,485
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(bctprd), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 4024.election 4028.election 4032.election 8008.election 8016.election 8024.election 8032.election 8040.election 8048.election 8056.election 8064.election 14014.election 14028.election 14042.election 14056.election 14070.election 14084.election 14098.election 14112.election 20020.election 20040.election 20060.election 20080.election 20100.election 20120.election 20140.election 20160.election 22022.election 22044.election 22066.election 22088.election 22110.election 22132.election 22154.election 22176.election 24072.election 24096.election 24120.election 24144.election 24168.election 24192.election 26026.election 26052.election 26078.election 26104.election 26130.election 26156.election 26182.election 26208.election 34034.election 34068.election 34102.election 34136.election 34170.election 34204.election 34238.election 34272.election 46046.election 46092.election 46138.election 46184.election 46230.election 46276.election 46322.election 46368.election 48048.election 48096.election 48144.election 48192.election 48240.election 48288.election 48336.election 48384.election 52052.election 52104.election 52156.election 52208.election 52260.election 52312.election 52364.election 52416.election 56056.election 56112.election 56168.election 56224.election 56280.election 56336.election 56392.election 56448.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} .0361116{col 29}{space 2} .0027606{col 40}{space 1}   13.08{col 49}{space 3}0.000{col 57}{space 4}  .030701{col 70}{space 3} .0415222
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2}-.0336077{col 29}{space 2} .0023355{col 40}{space 1}  -14.39{col 49}{space 3}0.000{col 57}{space 4}-.0381853{col 70}{space 3}-.0290301
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{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.0093638{col 29}{space 2} .0103631{col 40}{space 1}   -0.90{col 49}{space 3}0.366{col 57}{space 4}-.0296752{col 70}{space 3} .0109475
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{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .0012963{col 29}{space 2} .0093853{col 40}{space 1}    0.14{col 49}{space 3}0.890{col 57}{space 4}-.0170987{col 70}{space 3} .0196912
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.0331794{col 29}{space 2} .0013767{col 40}{space 1}  -24.10{col 49}{space 3}0.000{col 57}{space 4}-.0358776{col 70}{space 3}-.0304812
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{txt}{space 9}48096  {c |}{col 17}{res}{space 2}  .092107{col 29}{space 2} .0024671{col 40}{space 1}   37.33{col 49}{space 3}0.000{col 57}{space 4} .0872714{col 70}{space 3} .0969425
{txt}{space 9}48144  {c |}{col 17}{res}{space 2} .1068645{col 29}{space 2} .0024484{col 40}{space 1}   43.65{col 49}{space 3}0.000{col 57}{space 4} .1020656{col 70}{space 3} .1116633
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{txt}{space 9}52052  {c |}{col 17}{res}{space 2}-.0736093{col 29}{space 2} .0035265{col 40}{space 1}  -20.87{col 49}{space 3}0.000{col 57}{space 4}-.0805211{col 70}{space 3}-.0666975
{txt}{space 9}52104  {c |}{col 17}{res}{space 2}-.1040472{col 29}{space 2} .0026524{col 40}{space 1}  -39.23{col 49}{space 3}0.000{col 57}{space 4}-.1092459{col 70}{space 3}-.0988485
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{txt}{space 9}56336  {c |}{col 17}{res}{space 2}  .309695{col 29}{space 2} .0012595{col 40}{space 1}  245.88{col 49}{space 3}0.000{col 57}{space 4} .3072264{col 70}{space 3} .3121636
{txt}{space 9}56392  {c |}{col 17}{res}{space 2} .3470316{col 29}{space 2} .0021284{col 40}{space 1}  163.05{col 49}{space 3}0.000{col 57}{space 4}   .34286{col 70}{space 3} .3512032
{txt}{space 9}56448  {c |}{col 17}{res}{space 2} .3465574{col 29}{space 2} .0028804{col 40}{space 1}  120.32{col 49}{space 3}0.000{col 57}{space 4}  .340912{col 70}{space 3} .3522029
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b7
{txt}
{com}. 
. logit mmbprty i.GL i.gender agea eduyrs swi i.employ i.rural i.election if fulldata==1 & partner==1 [pw=weight], robust cluster(cntry)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-12410.177}  
Iteration 1:{space 3}log pseudolikelihood = {res:-11720.746}  
Iteration 2:{space 3}log pseudolikelihood = {res:-11537.718}  
Iteration 3:{space 3}log pseudolikelihood = {res:-11536.762}  
Iteration 4:{space 3}log pseudolikelihood = {res:-11536.762}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}    69,023
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(10)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-11536.762{txt}{col 49}Pseudo R2{col 67}= {res}    0.0704

{txt}{ralign 81:(Std. Err. adjusted for {res:12} clusters in cntry)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}        mmbprty{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2} -.059865{col 29}{space 2} .1779766{col 40}{space 1}   -0.34{col 49}{space 3}0.737{col 57}{space 4}-.4086927{col 70}{space 3} .2889627
{txt}{space 15} {c |}
{space 9}gender {c |}
{space 10}Male  {c |}{col 17}{res}{space 2}  .552087{col 29}{space 2} .0952002{col 40}{space 1}    5.80{col 49}{space 3}0.000{col 57}{space 4}  .365498{col 70}{space 3} .7386759
{txt}{space 11}agea {c |}{col 17}{res}{space 2} .0354203{col 29}{space 2} .0052153{col 40}{space 1}    6.79{col 49}{space 3}0.000{col 57}{space 4} .0251984{col 70}{space 3} .0456421
{txt}{space 9}eduyrs {c |}{col 17}{res}{space 2} .0617007{col 29}{space 2} .0124315{col 40}{space 1}    4.96{col 49}{space 3}0.000{col 57}{space 4} .0373355{col 70}{space 3} .0860659
{txt}{space 12}swi {c |}{col 17}{res}{space 2} .1359781{col 29}{space 2} .0403959{col 40}{space 1}    3.37{col 49}{space 3}0.001{col 57}{space 4} .0568035{col 70}{space 3} .2151527
{txt}{space 15} {c |}
{space 9}employ {c |}
{space 4}Job-seeker  {c |}{col 17}{res}{space 2}-.1221035{col 29}{space 2} .1863689{col 40}{space 1}   -0.66{col 49}{space 3}0.512{col 57}{space 4}-.4873798{col 70}{space 3} .2431727
{txt}{space 6}Studying  {c |}{col 17}{res}{space 2} .3210413{col 29}{space 2}  .175764{col 40}{space 1}    1.83{col 49}{space 3}0.068{col 57}{space 4}-.0234499{col 70}{space 3} .6655325
{txt}{space 10}NIWF  {c |}{col 17}{res}{space 2}-.1642785{col 29}{space 2} .1286599{col 40}{space 1}   -1.28{col 49}{space 3}0.202{col 57}{space 4}-.4164472{col 70}{space 3} .0878902
{txt}{space 7}Retired  {c |}{col 17}{res}{space 2}-.1698112{col 29}{space 2}   .05711{col 40}{space 1}   -2.97{col 49}{space 3}0.003{col 57}{space 4}-.2817447{col 70}{space 3}-.0578777
{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .2274362{col 29}{space 2} .1154837{col 40}{space 1}    1.97{col 49}{space 3}0.049{col 57}{space 4} .0010923{col 70}{space 3} .4537801
{txt}{space 15} {c |}
{space 7}election {c |}
{space 10}4008  {c |}{col 17}{res}{space 2}-.0601435{col 29}{space 2} .0113277{col 40}{space 1}   -5.31{col 49}{space 3}0.000{col 57}{space 4}-.0823453{col 70}{space 3}-.0379417
{txt}{space 10}4012  {c |}{col 17}{res}{space 2}-.1565035{col 29}{space 2} .0200956{col 40}{space 1}   -7.79{col 49}{space 3}0.000{col 57}{space 4}-.1958901{col 70}{space 3}-.1171169
{txt}{space 10}4016  {c |}{col 17}{res}{space 2}-.5456008{col 29}{space 2} .0204473{col 40}{space 1}  -26.68{col 49}{space 3}0.000{col 57}{space 4}-.5856767{col 70}{space 3}-.5055249
{txt}{space 10}4020  {c |}{col 17}{res}{space 2}-.3928008{col 29}{space 2}  .022072{col 40}{space 1}  -17.80{col 49}{space 3}0.000{col 57}{space 4}-.4360611{col 70}{space 3}-.3495406
{txt}{space 10}8008  {c |}{col 17}{res}{space 2} .2829116{col 29}{space 2} .0164535{col 40}{space 1}   17.19{col 49}{space 3}0.000{col 57}{space 4} .2506633{col 70}{space 3} .3151598
{txt}{space 10}8016  {c |}{col 17}{res}{space 2} .1466941{col 29}{space 2} .0213126{col 40}{space 1}    6.88{col 49}{space 3}0.000{col 57}{space 4} .1049221{col 70}{space 3} .1884661
{txt}{space 10}8024  {c |}{col 17}{res}{space 2}-.1270361{col 29}{space 2} .0328106{col 40}{space 1}   -3.87{col 49}{space 3}0.000{col 57}{space 4}-.1913438{col 70}{space 3}-.0627285
{txt}{space 10}8032  {c |}{col 17}{res}{space 2} -.213952{col 29}{space 2} .0123919{col 40}{space 1}  -17.27{col 49}{space 3}0.000{col 57}{space 4}-.2382396{col 70}{space 3}-.1896643
{txt}{space 10}8040  {c |}{col 17}{res}{space 2}-.1499444{col 29}{space 2} .0189683{col 40}{space 1}   -7.91{col 49}{space 3}0.000{col 57}{space 4}-.1871215{col 70}{space 3}-.1127673
{txt}{space 9}14014  {c |}{col 17}{res}{space 2}-.7962542{col 29}{space 2} .0335352{col 40}{space 1}  -23.74{col 49}{space 3}0.000{col 57}{space 4} -.861982{col 70}{space 3}-.7305264
{txt}{space 9}14028  {c |}{col 17}{res}{space 2}-1.173655{col 29}{space 2} .0327064{col 40}{space 1}  -35.88{col 49}{space 3}0.000{col 57}{space 4}-1.237759{col 70}{space 3}-1.109552
{txt}{space 9}14042  {c |}{col 17}{res}{space 2}-.7747801{col 29}{space 2} .0391743{col 40}{space 1}  -19.78{col 49}{space 3}0.000{col 57}{space 4}-.8515603{col 70}{space 3}-.6979998
{txt}{space 9}14056  {c |}{col 17}{res}{space 2}-1.180512{col 29}{space 2} .0390884{col 40}{space 1}  -30.20{col 49}{space 3}0.000{col 57}{space 4}-1.257124{col 70}{space 3}  -1.1039
{txt}{space 9}14070  {c |}{col 17}{res}{space 2}-.9623502{col 29}{space 2} .0334515{col 40}{space 1}  -28.77{col 49}{space 3}0.000{col 57}{space 4}-1.027914{col 70}{space 3}-.8967865
{txt}{space 9}20020  {c |}{col 17}{res}{space 2}-.7829463{col 29}{space 2} .0362743{col 40}{space 1}  -21.58{col 49}{space 3}0.000{col 57}{space 4}-.8540426{col 70}{space 3}  -.71185
{txt}{space 9}20040  {c |}{col 17}{res}{space 2}-.7555697{col 29}{space 2} .0259977{col 40}{space 1}  -29.06{col 49}{space 3}0.000{col 57}{space 4}-.8065243{col 70}{space 3}-.7046151
{txt}{space 9}20060  {c |}{col 17}{res}{space 2}-1.265904{col 29}{space 2} .0252147{col 40}{space 1}  -50.21{col 49}{space 3}0.000{col 57}{space 4}-1.315324{col 70}{space 3}-1.216484
{txt}{space 9}20080  {c |}{col 17}{res}{space 2}-1.795469{col 29}{space 2} .0276121{col 40}{space 1}  -65.02{col 49}{space 3}0.000{col 57}{space 4}-1.849588{col 70}{space 3}-1.741351
{txt}{space 9}20100  {c |}{col 17}{res}{space 2}-1.562147{col 29}{space 2} .0233731{col 40}{space 1}  -66.84{col 49}{space 3}0.000{col 57}{space 4}-1.607958{col 70}{space 3}-1.516337
{txt}{space 9}22022  {c |}{col 17}{res}{space 2} .1165275{col 29}{space 2}  .025342{col 40}{space 1}    4.60{col 49}{space 3}0.000{col 57}{space 4} .0668582{col 70}{space 3} .1661969
{txt}{space 9}22044  {c |}{col 17}{res}{space 2}-.1104224{col 29}{space 2} .0218594{col 40}{space 1}   -5.05{col 49}{space 3}0.000{col 57}{space 4}-.1532661{col 70}{space 3}-.0675788
{txt}{space 9}22066  {c |}{col 17}{res}{space 2} -.193483{col 29}{space 2} .0202369{col 40}{space 1}   -9.56{col 49}{space 3}0.000{col 57}{space 4}-.2331466{col 70}{space 3}-.1538193
{txt}{space 9}22088  {c |}{col 17}{res}{space 2}-.2170976{col 29}{space 2} .0171982{col 40}{space 1}  -12.62{col 49}{space 3}0.000{col 57}{space 4}-.2508055{col 70}{space 3}-.1833897
{txt}{space 9}22110  {c |}{col 17}{res}{space 2}-.2532282{col 29}{space 2} .0249743{col 40}{space 1}  -10.14{col 49}{space 3}0.000{col 57}{space 4}-.3021769{col 70}{space 3}-.2042795
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{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-5.722215{col 29}{space 2} .4382885{col 40}{space 1}  -13.06{col 49}{space 3}0.000{col 57}{space 4}-6.581245{col 70}{space 3}-4.863185
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store a8
{txt}
{com}. margins, dydx(*) post
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    69,023
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(mmbprty), predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:1.GL 1.gender agea eduyrs swi 2.employ 3.employ 4.employ 5.employ 1.rural 4008.election 4012.election 4016.election 4020.election 8008.election 8016.election 8024.election 8032.election 8040.election 14014.election 14028.election 14042.election 14056.election 14070.election 20020.election 20040.election 20060.election 20080.election 20100.election 22022.election 22044.election 22066.election 22088.election 22110.election 24072.election 24096.election 24120.election 26026.election 26052.election 26078.election 26104.election 26130.election 34034.election 34068.election 34102.election 34136.election 34170.election 46046.election 46092.election 46138.election 46184.election 46230.election 48048.election 48096.election 48144.election 48192.election 48240.election 52052.election 52104.election 52156.election 52208.election 52260.election 56056.election 56112.election 56168.election 56224.election 56280.election}{p_end}
{p2colreset}{...}

{res}{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29} Delta-method
{col 17}{c |}      dy/dx{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}GL {c |}
Gay or Lesbian  {c |}{col 17}{res}{space 2}-.0021441{col 29}{space 2} .0062155{col 40}{space 1}   -0.34{col 49}{space 3}0.730{col 57}{space 4}-.0143262{col 70}{space 3}  .010038
{txt}{space 15} {c |}
{space 9}gender {c |}
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{txt}{space 15} {c |}
{space 9}employ {c |}
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{txt}{space 15} {c |}
{space 8}1.rural {c |}{col 17}{res}{space 2} .0085137{col 29}{space 2} .0043937{col 40}{space 1}    1.94{col 49}{space 3}0.053{col 57}{space 4}-.0000978{col 70}{space 3} .0171251
{txt}{space 15} {c |}
{space 7}election {c |}
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{p 0 6 0 81}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. estimates store b8
{txt}
{com}. 
. 
. coefplot b1 || b2 || b3 || b8 || b6 || b5 || b7 || b4, keep(*.GL) xline(0) mlabel rescale(100) format(%9.2g) mlabposition(2) mlabgap(*2) ci(95 90) byopts(row(4))
{res}{txt}
{com}. 
. 
. 
. 
{txt}end of do-file

{com}. log close
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 {txt}closed on:  {res}24 Jul 2020, 14:31:17
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